[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-76060":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":14,"subscribersCount":14,"size":14,"stars1d":14,"stars7d":14,"stars30d":15,"stars90d":14,"forks30d":14,"starsTrendScore":14,"compositeScore":16,"rankGlobal":10,"rankLanguage":10,"license":10,"archived":17,"fork":17,"defaultBranch":18,"hasWiki":19,"hasPages":17,"topics":20,"createdAt":10,"pushedAt":10,"updatedAt":34,"readmeContent":35,"aiSummary":36,"trendingCount":14,"starSnapshotCount":14,"syncStatus":37,"lastSyncTime":38,"discoverSource":39},76060,"Awesome-Datasets-Hub","ahammadmejbah\u002FAwesome-Datasets-Hub","ahammadmejbah","A curated collection of datasets for Large Language Models (LLMs), covering medical AI, NLP, multimodal learning, instruction tuning, reasoning, code generation, and evaluation benchmarks.","https:\u002F\u002Fintelligenceacademy.ai\u002Fdatasets",null,136,39,1,0,29,4.81,false,"main",true,[21,22,23,24,25,26,27,28,29,30,31,32,33],"benchmark","benchmarking","deep-learning","deep-neural-networks","deeplearning","genetic-algorithm","llm","llm-evaluation","llm-inference","machine-learning","machine-learning-algorithms","machinelearning","neural-network","2026-06-12 02:03:39","\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Fahammadmejbah\u002FAwesome-LLM-Datasets\u002Fblob\u002Fmain\u002FBanner.jpeg\" class=\"center-img\" alt=\"Description\">\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"mailto:ahammadmejbah@gmail.com\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEmail-ahammadmejbah%40gmail.com-blue?style=flat-square&logo=gmail\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fahammadmejbah\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGitHub-%40ahammadmejbah-lightgrey?style=flat-square&logo=github\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Flinkedin.com\u002Fin\u002Fahammadmejbah\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLinkedIn-Mejbah%20Ahammad-blue?style=flat-square&logo=linkedin\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fintelligenceacademy.ai\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWebsite-Intelligence%20of%20Academy-lightgrey?style=flat-square&logo=google-chrome\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002F@IntelligenceAcademy\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FYouTube-IntelligenceAcademy-red?style=flat-square&logo=youtube\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FMejbah-Ahammad-2\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearchGate-Mejbah%20Ahammad-blue?style=flat-square&logo=researchgate\">\u003C\u002Fa>\n  \u003Cbr>\n  \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhone-%2B8801874603631-green?style=flat-square&logo=whatsapp\">\n  \u003Ca href=\"https:\u002F\u002Fwww.hackerrank.com\u002Fprofile\u002Fahammadmejbah\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FHackerrank-ahammadmejbah-green?style=flat-square&logo=hackerrank\">\u003C\u002Fa>\n\n\u003C\u002Fp>\n\n\u003Cdiv align=\"center\">\n\n## ⚡ Medical Datasets for LLM\n| Serial | Dataset | Domain | Field \u002F Task | Scale | Strength | Language | License |\n|---|---|---|---|---|---|---|---|\n| **01** | [**MedQA (USMLE)**](https:\u002F\u002Fgithub.com\u002Fjind11\u002FMedQA) \u003Cbr>\u003Csub>Jin et al. · 2021\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Medical QA · Licensing Exam | **12,723 Q** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN\u002FZH\u002FTW](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN%20%7C%20ZH%20%7C%20TW-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **02** | [**MedMCQA**](https:\u002F\u002Fmedmcqa.github.io) \u003Cbr>\u003Csub>Pal et al. · 2022\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Medical MCQ · Indian Licensing | **194K Q** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **03** | [**PubMedQA**](https:\u002F\u002Fpubmedqa.github.io) \u003Cbr>\u003Csub>Jin et al. · 2019\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Biomedical QA · Yes\u002FNo\u002FMaybe | **273K QA** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **04** | [**BioASQ**](https:\u002F\u002Fbmcbioinformatics.biomedcentral.com\u002Farticles\u002F10.1186\u002Fs12859-017-1703-7) \u003Cbr>\u003Csub>Tsatsaronis et al.\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Biomedical QA · Semantic Indexing | **5,600+ Q** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY%202.5-0D5FA6?style=flat-square) |\n| **05** | [**MASH-QA**](https:\u002F\u002Fgithub.com\u002Fmingzhu0527\u002FMASHQA) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Healthcare QA · Multi-span | **35K QA** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **06** | [**MedQuAD**](https:\u002F\u002Fgithub.com\u002Fabachaa\u002FMedQuAD) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Consumer Medical QA | **47K QA** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY%204.0-0D5FA6?style=flat-square) |\n| **07** | [**LiveQA Medical**](https:\u002F\u002Fgithub.com\u002Fabachaa\u002FLiveQA_MedicalTask_TREC2017) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Consumer Health QA | **634 Q** | ![6\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F6%2F10-b45309?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **08** | [**MedS-Bench**](https:\u002F\u002Fhenrychur.github.io\u002FMedS-Bench\u002F) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | Clinical Evaluation | **13 tasks** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Apache](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FApache%202.0-22863a?style=flat-square) |\n| **09** | [**COVID-QA**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fdeepset\u002Fcovid_qa_deepset) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-7c3aed?style=flat-square) | COVID-19 Reading QA | **2,019 QA** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **10** | [**MIMIC-III**](https:\u002F\u002Fphysionet.org\u002Fcontent\u002Fmimiciii\u002F) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | ICU EHR + Clinical Notes | **46K patients** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![DUA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet%20DUA-dc2626?style=flat-square) |\n| **11** | [**MIMIC-IV**](https:\u002F\u002Fphysionet.org\u002Fcontent\u002Fmimiciv\u002F) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Hospital EHR Records | **299K patients** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![DUA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet%20DUA-dc2626?style=flat-square) |\n| **12** | [**n2c2 \u002F i2b2 Challenges**](https:\u002F\u002Fn2c2.dbmi.hms.harvard.edu) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical NLP Challenges | **Multi-year** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![DUA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDUA-dc2626?style=flat-square) |\n| **13** | [**MedNLI**](https:\u002F\u002Fphysionet.org\u002Fcontent\u002Fmednli\u002F) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical Textual Entailment | **14K pairs** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![DUA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet%20DUA-dc2626?style=flat-square) |\n| **14** | [**emrQA**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fbigbio\u002Femrqa) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical QA over EHR | **1M+ QA** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMIT-22863a?style=flat-square) |\n| **15** | [**MTSamples**](https:\u002F\u002Fmtsamples.com) | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical Transcription Notes | **5K+ reports** | ![6\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F6%2F10-b45309?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square) |\n| **16** | [**EHRNoteQA**](https:\u002F\u002Fphysionet.org\u002Fcontent\u002Fehrnoteqa\u002F) \u003Cbr>\u003Csub>PhysioNet · 2023\u003C\u002Fsub> | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical Note Question Answering | **2.4K QA** | ![6\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F6%2F10-b45309?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![PhysioNet](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet-dc2626?style=flat-square) |\n| **17** | [**Asclepius**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fstarmpcc\u002FAsclepius-Synthetic-Clinical-Notes) \u003Cbr>\u003Csub>STAR-MPCC · 2023\u003C\u002Fsub> | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Synthetic Clinical Notes | **158K Notes** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY-0D5FA6?style=flat-square) |\n| **18** | [**GatorTron Corpus**](https:\u002F\u002Farxiv.org\u002Fabs\u002F2305.13523) \u003Cbr>\u003Csub>University of Florida · 2023\u003C\u002Fsub> | ![Clinical NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FClinical%20NLP-1d4ed8?style=flat-square) | Clinical Language Model Pretraining | **90B Words** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Restricted](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRestricted-b45309?style=flat-square) |\n| **19** | [**CORD-19**](https:\u002F\u002Fgithub.com\u002Fallenai\u002Fcord19) \u003Cbr>\u003Csub>AllenAI · 2020\u003C\u002Fsub> | ![Biomedical](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBiomedical-4338ca?style=flat-square) | COVID-19 Scientific Literature | **1M+ Papers** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Custom](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCustom-6366f1?style=flat-square) |\n| **20** | [**PMC-OA**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Faxiong\u002Fpmc_oa) \u003Cbr>\u003Csub>PubMed Central\u003C\u002Fsub> | ![Biomedical](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBiomedical-4338ca?style=flat-square) | Biomedical Literature Pretraining | **4M+ Articles** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Open Access](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen%20Access-22863a?style=flat-square) |\n| **21** | [**PMC-LLaMA Data**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Faxiong\u002FPMC_LLaMA_instructions) \u003Cbr>\u003Csub>PMC-LLaMA · 2023\u003C\u002Fsub> | ![Biomedical](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBiomedical-4338ca?style=flat-square) | Medical Instruction Tuning | **75B Tokens** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Open Access](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen%20Access-22863a?style=flat-square) |\n| **22** | [**PMC-Patients**](https:\u002F\u002Fpmc-patients.github.io\u002F) \u003Cbr>\u003Csub>NCATS · 2022\u003C\u002Fsub> | ![Biomedical](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBiomedical-4338ca?style=flat-square) | Patient-Friendly Summaries | **167K Patients** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY-0D5FA6?style=flat-square) |\n| **23** | [**MIMIC-CXR**](https:\u002F\u002Fphysionet.org\u002Fcontent\u002Fmimic-cxr\u002F) \u003Cbr>\u003Csub>PhysioNet · 2019\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Chest X-ray + Radiology Reports | **377K Images** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![PhysioNet](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet-dc2626?style=flat-square) |\n| **24** | [**CheXpert**](https:\u002F\u002Fstanfordmlgroup.github.io\u002Fcompetitions\u002Fchexpert\u002F) \u003Cbr>\u003Csub>Stanford ML Group · 2019\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | X-ray Classification | **224K Images** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **25** | [**NIH ChestX-ray14**](https:\u002F\u002Fnihcc.app.box.com\u002Fv\u002FChestXray-NIHCC) \u003Cbr>\u003Csub>NIH · 2017\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Thoracic Disease Detection | **112K Images** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC0](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC0-22863a?style=flat-square) |\n| **26** | [**OpenI**](https:\u002F\u002Fopeni.nlm.nih.gov\u002F) \u003Cbr>\u003Csub>National Library of Medicine\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Radiology Reports & Images | **7K Cases** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square) |\n| **27** | [**ROCO**](https:\u002F\u002Fgithub.com\u002Frazorx89\u002Froco-dataset) \u003Cbr>\u003Csub>ROCO Team · 2020\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Medical Vision-Language | **81K Images** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Multi](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMulti-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **28** | [**PadChest**](https:\u002F\u002Fbimcv.cipf.es\u002Fbimcv-projects\u002Fpadchest\u002F) \u003Cbr>\u003Csub>BIMCV · 2019\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Chest X-ray Interpretation | **160K Images** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![ES\u002FEN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FES%20%7C%20EN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **29** | [**VinDr-CXR**](https:\u002F\u002Fvindr.ai\u002Fcxr) \u003Cbr>\u003Csub>VinBigData · 2021\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Chest X-ray Abnormality Detection | **18K Images** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![PhysioNet](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPhysioNet-dc2626?style=flat-square) |\n| **30** | [**RSNA Pneumonia**](https:\u002F\u002Fwww.kaggle.com\u002Fc\u002Frsna-pneumonia-detection-challenge) \u003Cbr>\u003Csub>RSNA · 2018\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Pneumonia Detection | **30K Images** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square) |\n| **31** | [**BraTS**](https:\u002F\u002Fwww.med.upenn.edu\u002Fcbica\u002Fbrats2021\u002F) \u003Cbr>\u003Csub>MICCAI · 2021\u003C\u002Fsub> | ![Radiology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRadiology-dc2626?style=flat-square) | Brain Tumor Segmentation | **2K+ MRI Scans** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![Multi](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMulti-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **32** | [**MedMentions**](https:\u002F\u002Fgithub.com\u002Fchanzuckerberg\u002FMedMentions) \u003Cbr>\u003Csub>Chan Zuckerberg Initiative · 2019\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Biomedical Named Entity Recognition | **4K Abstracts** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY-0D5FA6?style=flat-square) |\n| **33** | [**BC5CDR**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fbigbio\u002Fbc5cdr) \u003Cbr>\u003Csub>BioCreative V · 2015\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Chemical & Disease NER | **1,500 Articles** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **34** | [**NCBI Disease Corpus**](https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002FCBBresearch\u002FDogan\u002FDISEASE\u002F) \u003Cbr>\u003Csub>NCBI · 2014\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Disease Entity Recognition | **793 Abstracts** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square) |\n| **35** | [**DDI Corpus**](https:\u002F\u002Fgithub.com\u002Fisegura\u002FDDICorpus) \u003Cbr>\u003Csub>SemEval · 2013\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Drug-Drug Interaction Extraction | **1K Documents** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **36** | [**ADE Corpus**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fade_corpus_v2) \u003Cbr>\u003Csub>ADE Corpus · 2012\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Adverse Drug Event Extraction | **4K+ Sentences** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY-0D5FA6?style=flat-square) |\n| **37** | [**JNLPBA**](https:\u002F\u002Fgithub.com\u002Fspyysalo\u002Fjnlpba) \u003Cbr>\u003Csub>GENIA Project · 2004\u003C\u002Fsub> | ![NER](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNER%20%2F%20IE-0d9488?style=flat-square) | Biomedical Entity Recognition | **2K Abstracts** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **38** | [**MedDialog**](https:\u002F\u002Fgithub.com\u002FLireanstar\u002FMedical-Dialogue-Corpus) \u003Cbr>\u003Csub>UCSD AI4H · 2020\u003C\u002Fsub> | ![Dialogue](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDialogue-db2777?style=flat-square) | Medical Dialogue Generation | **1M Conversations** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![ZH\u002FEN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FZH%20%7C%20EN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **39** | [**HealthCareMagic-100K**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fwangrongsheng\u002FHealthCareMagic-100k-en) \u003Cbr>\u003Csub>LaViTa · 2023\u003C\u002Fsub> | ![Dialogue](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDialogue-db2777?style=flat-square) | Doctor-Patient Conversation | **100K Dialogues** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Custom](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCustom-6366f1?style=flat-square) |\n| **40** | [**iCliniq**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002FzhengComing\u002FiCliniq-10K) \u003Cbr>\u003Csub>LaViTa · 2023\u003C\u002Fsub> | ![Dialogue](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDialogue-db2777?style=flat-square) | Clinical Consultation Dialogue | **10K Dialogues** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Custom](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCustom-6366f1?style=flat-square) |\n| **41** | [**MeQSum**](https:\u002F\u002Fgithub.com\u002Fabachaa\u002FMeQSum) \u003Cbr>\u003Csub>Mayo Clinic · 2019\u003C\u002Fsub> | ![Dialogue](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDialogue-db2777?style=flat-square) | Medical Question Summarization | **1K Questions** | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **42** | [**Medical Meadow**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Fmedalpaca\u002Fmedical_meadow_medical_flashcards) \u003Cbr>\u003Csub>MedAlpaca · 2023\u003C\u002Fsub> | ![Instruction](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FInstruction-ea580c?style=flat-square) | Medical Instruction Tuning | **Millions of Samples** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Apache](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FApache%202.0-22863a?style=flat-square) |\n| **43** | [**MedInstruct-52K**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002Flavita\u002FAlpaCare-MedInstruct-52k) \u003Cbr>\u003Csub>WangLab · 2023\u003C\u002Fsub> | ![Instruction](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FInstruction-ea580c?style=flat-square) | Medical Instruction Following | **52K Instructions** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n| **44** | [**MedC-I**](https:\u002F\u002Fmedci.com\u002F) \u003Cbr>\u003Csub>MedC-I Team · 2024\u003C\u002Fsub> | ![Instruction](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FInstruction-ea580c?style=flat-square) | Clinical Instruction Tuning | **100K+ Samples** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Apache](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FApache%202.0-22863a?style=flat-square) |\n| **45** | [**DrugBank**](https:\u002F\u002Fgo.drugbank.com\u002Freleases\u002Flatest) \u003Cbr>\u003Csub>DrugBank · 2024\u003C\u002Fsub> | ![Pharmacology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPharmacology-d97706?style=flat-square) | Drug Discovery & Interaction Knowledge | **17K+ Drugs** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![Commercial](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCommercial-dc2626?style=flat-square) |\n| **46** | [**SIDER**](https:\u002F\u002Fsideeffects.embl.de\u002F) \u003Cbr>\u003Csub>EMBL · 2016\u003C\u002Fsub> | ![Pharmacology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPharmacology-d97706?style=flat-square) | Drug Side Effect Extraction | **143K Side Effects** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![CC BY](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCC%20BY-0D5FA6?style=flat-square) |\n| **47** | [**FDA Drug Labels (SPL)**](https:\u002F\u002Fopen.fda.gov\u002Fapis\u002Fdrug\u002Flabel\u002F) \u003Cbr>\u003Csub>FDA · 2024\u003C\u002Fsub> | ![Pharmacology](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPharmacology-d97706?style=flat-square) | Structured Pharmaceutical Labels | **150K+ Labels** | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![EN](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEN-lightgrey?style=flat-square) | ![OpenFDA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpenFDA-22863a?style=flat-square) |\n| **48** | [**TCGA**](https:\u002F\u002Fwww.cancer.gov\u002Fccg\u002Fresearch\u002Fgenome-sequencing\u002Ftcga) \u003Cbr>\u003Csub>National Cancer Institute\u003C\u002Fsub> | ![Genomics](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenomics-16a34a?style=flat-square) | Cancer Genomics & Multi-omics | **20K+ Patients** | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![Multi](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMulti-lightgrey?style=flat-square) | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square) |\n| **49** | [**CMB**](https:\u002F\u002Fgithub.com\u002FFreedomIntelligence\u002FCMB) \u003Cbr>\u003Csub>Freedom Intelligence · 2023\u003C\u002Fsub> | ![Multilingual](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMultilingual-6366f1?style=flat-square) | Chinese Medical Benchmark | **20K Questions** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![ZH](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FZH-lightgrey?style=flat-square) | ![Apache](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FApache%202.0-22863a?style=flat-square) |\n| **50** | [**CLEF eHealth**](https:\u002F\u002Fclefehealth.imag.fr\u002F) \u003Cbr>\u003Csub>CLEF Initiative\u003C\u002Fsub> | ![Multilingual](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMultilingual-6366f1?style=flat-square) | Multilingual Medical Information Retrieval | **Multi-Year Tasks** | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Multi](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMulti-lightgrey?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) |\n\u003C\u002Fdiv>\n\n\u003C\u002Fbr>\n\u003C\u002Fbr>\n\n\u003Cdiv align=\"center\">\n\n## ⚡ VLSI (Very Large-Scale Integration) Datasets\n\n| Serial  | Dataset | Domain | Field \u002F Task | Scale | Strength | Type | Source |\n|---|---|---|---|---|---|---|---|\n| **01** | [**HKUST-GZ Design Dataset**](https:\u002F\u002Fgithub.com\u002FHKUST-GZ-VLSI\u002FDesign-Dataset) \u003Cbr>\u003Csub>HKUST-GZ VLSI Lab\u003C\u002Fsub> | ![EDA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEDA-2563eb?style=flat-square) | Physical Design & Routing | Multi-design benchmark | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square&label=Strength) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square) | GitHub |\n| **02** | [**University of Waterloo VLSI Dataset**](https:\u002F\u002Fwww.math.uwaterloo.ca\u002Ftsp\u002Fvlsi\u002Findex.html) \u003Cbr>\u003Csub>University of Waterloo\u003C\u002Fsub> | ![Optimization](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOptimization-7c3aed?style=flat-square) | Traveling Salesman for VLSI | Multiple benchmark graphs | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-b45309?style=flat-square) | Academic |\n| **03** | [**Calcite Test Dataset**](https:\u002F\u002Fgithub.com\u002Fvlsi\u002Fcalcite-test-dataset) \u003Cbr>\u003Csub>VLSI Research Community\u003C\u002Fsub> | ![Routing](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRouting-dc2626?style=flat-square) | Placement & Routing Validation | Test circuits | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square) | GitHub |\n| **04** | [**Rajasrl VLSI Dataset**](https:\u002F\u002Fhuggingface.co\u002Fdatasets\u002FRajasrl\u002FVLSI-Dataset) \u003Cbr>\u003Csub>Hugging Face\u003C\u002Fsub> | ![ML](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FML%20for%20EDA-db2777?style=flat-square) | Machine Learning for VLSI | Structured dataset | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![HF](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FHuggingFace-f59e0b?style=flat-square) | HuggingFace |\n| **05** | [**VLSI Circuit Parameter Dataset**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fbenin007\u002Fvlsi-circuit-parameter-dataset-for-ml) \u003Cbr>\u003Csub>Kaggle\u003C\u002Fsub> | ![Circuit](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCircuit-16a34a?style=flat-square) | Circuit Parameter Prediction | ML-ready tabular data | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square) | Kaggle |\n| **06** | [**Open Circuit Benchmark Suite**](https:\u002F\u002Fwww.samyzaf.com\u002FML\u002Fopens\u002Fopens.html) \u003Cbr>\u003Csub>OpenS Benchmark\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-6366f1?style=flat-square) | Circuit Optimization | Open benchmark circuits | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square) | Research |\n| **07** | [**Roboflow VLSI Dataset**](https:\u002F\u002Funiverse.roboflow.com\u002Faruns-workspace-8mqby\u002Fvlsi) \u003Cbr>\u003Csub>Roboflow Universe\u003C\u002Fsub> | ![Computer Vision](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FComputer%20Vision-0d9488?style=flat-square) | VLSI Image\u002FObject Detection | Annotated visual dataset | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Vision](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVision-dc2626?style=flat-square) | Roboflow |\n| **08** | [**VLSI System Design Datasets**](https:\u002F\u002Fwww.vlsisystemdesign.com\u002Ftag\u002Fdata-sets\u002F) \u003Cbr>\u003Csub>VSD Corp\u003C\u002Fsub> | ![Education](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEducation-f97316?style=flat-square) | EDA Learning & Benchmarks | Multiple datasets | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Educational](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEducational-2563eb?style=flat-square) | Web |\n| **09** | [**Waterloo VLSI Page 2**](https:\u002F\u002Fwww.math.uwaterloo.ca\u002Ftsp\u002Fvlsi\u002Fpage2.html) \u003Cbr>\u003Csub>University of Waterloo\u003C\u002Fsub> | ![Optimization](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOptimization-7c3aed?style=flat-square) | Advanced VLSI Optimization | Benchmark layouts | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-b45309?style=flat-square) | Academic |\n| **10** | [**Southampton VLSI Dataset**](https:\u002F\u002Feprints.soton.ac.uk\u002F385521\u002F) \u003Cbr>\u003Csub>University of Southampton\u003C\u002Fsub> | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-4338ca?style=flat-square) | VLSI Architecture Research | Academic dataset | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-b45309?style=flat-square) | Institutional |\n| **11** | [**IntelLabs FloorSet**](https:\u002F\u002Fgithub.com\u002FIntelLabs\u002FFloorSet) \u003Cbr>\u003Csub>Intel Labs\u003C\u002Fsub> | ![Floorplanning](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FFloorplanning-2563eb?style=flat-square) | Chip Floorplanning & Placement | Large benchmark suite | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square) | GitHub |\n| **12** | [**VLSI Design Projects**](https:\u002F\u002Fgithub.com\u002Framiomer94\u002FVLSI-design-projects) \u003Cbr>\u003Csub>Community Repository\u003C\u002Fsub> | ![Design](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVLSI%20Design-7c3aed?style=flat-square) | Digital & Analog Design Projects | Multiple projects | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Educational](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEducational-f97316?style=flat-square) | GitHub |\n| **13** | [**LeonidasY VLSI Design**](https:\u002F\u002Fgithub.com\u002FLeonidasY\u002Fvlsi-design) \u003Cbr>\u003Csub>Open Hardware Research\u003C\u002Fsub> | ![EDA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEDA-dc2626?style=flat-square) | VLSI Architecture & RTL Design | HDL-based repository | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![RTL](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRTL-0d9488?style=flat-square) | GitHub |\n| **14** | [**Open Circuit Benchmark Suite**](https:\u002F\u002Fsamyzaf.com\u002FML\u002Fopens\u002Fopens.html) \u003Cbr>\u003Csub>OpenS Benchmark\u003C\u002Fsub> | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-6366f1?style=flat-square) | Circuit Optimization Benchmarks | Open benchmark circuits | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square) | Research |\n| **15** | [**Parasitic Analysis of RLC Circuits**](https:\u002F\u002Fgithub.com\u002Fgnanesh-16\u002FPARASITIC_AnalysisOF-RLC-Circuits) \u003Cbr>\u003Csub>EDA Research Project\u003C\u002Fsub> | ![Circuit](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCircuit%20Analysis-16a34a?style=flat-square) | RLC Parasitic Analysis | Simulation datasets | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Simulation](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FSimulation-0D5FA6?style=flat-square) | GitHub |\n| **16** | [**Kaggle VLSI Dataset**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fhemanthhari\u002Fvlsi-data) \u003Cbr>\u003Csub>Kaggle Community\u003C\u002Fsub> | ![ML](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FML%20for%20EDA-db2777?style=flat-square) | Machine Learning for VLSI | Structured ML dataset | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square&label=Strength) | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square) | Kaggle |\n| **17** | [**The OpenROAD Project**](https:\u002F\u002Fgithub.com\u002FThe-OpenROAD-Project) \u003Cbr>\u003Csub>OpenROAD Team\u003C\u002Fsub> | ![EDA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEDA-2563eb?style=flat-square) | Autonomous RTL-to-GDSII Flow | Enterprise-scale framework | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square&label=Strength) | ![OpenSource](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen%20Source-22863a?style=flat-square) | GitHub |\n| **18** | [**ISPD Roboflow Dataset**](https:\u002F\u002Funiverse.roboflow.com\u002Fcasproject\u002Fispd) \u003Cbr>\u003Csub>Roboflow Universe\u003C\u002Fsub> | ![Computer Vision](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FComputer%20Vision-0d9488?style=flat-square) | ISPD Layout Detection & Vision Tasks | Annotated layout dataset | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square&label=Strength) | ![Vision](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVision-dc2626?style=flat-square) | Roboflow |\n\n\u003C\u002Fdiv>\n\n\n\n\n\n\n\n\n\n\n\n\n\u003Cdiv align=\"center\">\n\n  # 💻 Computer Science & Information Technology\n\n| Serial | Dataset                                                                                                                                        | Domain                                                                     | Field \u002F Task       | Scale          | Strength                                                                | Type                                                                            | Source    |\n| ------ | ---------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | ------------------ | -------------- | ----------------------------------------------------------------------- | ------------------------------------------------------------------------------- | --------- |\n| **01** | [**SQuAD Explorer**](https:\u002F\u002Frajpurkar.github.io\u002FSQuAD-explorer\u002F) \u003Cbr>\u003Csub>NLP Research\u003C\u002Fsub>                                                  | ![NLP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNLP-2563eb?style=flat-square)          | Question Answering | 100k+ Qs       | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | Rajpurkar |\n| **02** | [**COCO Dataset**](https:\u002F\u002Fcocodataset.org\u002F#download) \u003Cbr>\u003Csub>Vision Bench\u003C\u002Fsub>                                                              | ![CV](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVision-7c3aed?style=flat-square)        | Object Detection   | 330k Images    | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-4338ca?style=flat-square)     | Microsoft |\n| **03** | [**Stanford SNAP**](https:\u002F\u002Fsnap.stanford.edu\u002Fdata\u002F) \u003Cbr>\u003Csub>Graph Data\u003C\u002Fsub>                                                                 | ![Algo](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAlgorithms-dc2626?style=flat-square)  | Network Analysis   | Massive Graphs | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square)     | Stanford  |\n| **04** | [**CodeSearchNet**](https:\u002F\u002Fgithub.com\u002Fgithub\u002FCodeSearchNet) \u003Cbr>\u003Csub>Code Analysis\u003C\u002Fsub>                                                      | ![Code](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FProgramming-0d9488?style=flat-square) | Program Analysis   | 2M Functions   | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![GitHub](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGitHub-000000?style=flat-square)         | GitHub    |\n| **05** | [**Google Cluster Data**](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fcluster-data) \u003Cbr>\u003Csub>OS Traces\u003C\u002Fsub>                                                     | ![OS](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOS-4b5563?style=flat-square)            | Workload Traces    | Enterprise     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Enterprise](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEnterprise-2563eb?style=flat-square) | Google    |\n| **06** | [**IMDb Datasets**](https:\u002F\u002Fdatasets.imdbws.com\u002F) \u003Cbr>\u003Csub>Relational Data\u003C\u002Fsub>                                                               | ![DB](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDatabases-db2777?style=flat-square)     | Data Mining        | Millions       | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square)         | IMDb      |\n| **07** | [**CPU SPEC Dataset**](https:\u002F\u002Fgithub.com\u002Ffelixsteinke\u002Fcpu-spec-dataset) \u003Cbr>\u003Csub>Hardware\u003C\u002Fsub>                                               | ![Arch](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FArch-ea580c?style=flat-square)        | Perf Bench         | Tech Specs     | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | GitHub    |\n| **08** | [**Google Cloud Data**](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fcluster-data) \u003Cbr>\u003Csub>Cloud Traces\u003C\u002Fsub>                                                    | ![Cloud](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCloud-2563eb?style=flat-square)      | Resource Mgmt      | Global         | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | Google    |\n| **09** | [**SE Interview Qs**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fsyedmharis\u002Fsoftware-engineering-interview-questions-dataset) \u003Cbr>\u003Csub>Software Eng\u003C\u002Fsub> | ![SE](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FSoftware-6366f1?style=flat-square)      | Text Analysis      | Structured     | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Kaggle    |\n| **10** | [**ITSM Dataset**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fswapniljadhav96\u002Fitsm-dataset) \u003Cbr>\u003Csub>IT Service\u003C\u002Fsub>                                     | ![IT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIT-16a34a?style=flat-square)            | Ticketing Logs     | Operational    | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Kaggle    |\n| **11** | [**Cyber Security**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fteamincribo\u002Fcyber-security-attacks) \u003Cbr>\u003Csub>Intrusion\u003C\u002Fsub>                              | ![Sec](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FSecurity-dc2626?style=flat-square)     | Attack Patterns    | 40k+ rows      | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Kaggle    |\n| **12** | [**Archive.org**](https:\u002F\u002Farchive.org\u002Fdetails\u002Fdatasets) \u003Cbr>\u003Csub>Web Library\u003C\u002Fsub>                                                             | ![Web](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWeb-0d9488?style=flat-square)          | User Behavior      | Historical     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Public](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPublic-22863a?style=flat-square)         | Archive   |\n\n\u003C\u002Fdiv>\n\n\n\u003Cdiv align=\"center\">\n\n  # 🤖 Artificial Intelligence & Machine Learning\n\n| Serial | Dataset                                                                                                                                                           | Domain                                                                     | Field \u002F Task    | Scale         | Strength                                                                | Type                                                                          | Source   |\n| ------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | --------------- | ------------- | ----------------------------------------------------------------------- | ----------------------------------------------------------------------------- | -------- |\n| **13** | [**IEEE Power Multi-Source**](https:\u002F\u002Fieee-dataport.org\u002Fdocuments\u002Fpower-system-multi-source-events-dataset) \u003Cbr>\u003Csub>Electrical\u003C\u002Fsub>                             | ![Power](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPower-16a34a?style=flat-square)      | System Events   | Research Logs | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![IEEE](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIEEE-00629b?style=flat-square)           | IEEE     |\n| **14** | [**NREL Solar Power**](https:\u002F\u002Fwww.nrel.gov\u002Fgrid\u002Fsolar-power-data.html) \u003Cbr>\u003Csub>Renewables\u003C\u002Fsub>                                                                 | ![Energy](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRenewable-fbbf24?style=flat-square) | Solar Grid Data | National      | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)             | NREL     |\n| **15** | [**Smart Grid Monitor**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fziya07\u002Fsmart-grid-monitoring-dataset\u002Fdata) \u003Cbr>\u003Csub>Smart Grid\u003C\u002Fsub>                                     | ![Grid](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGrid-0ea5e9?style=flat-square)        | IoT Monitoring  | Real-time     | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)       | Kaggle   |\n| **16** | [**Industrial Machines**](https:\u002F\u002Fieee-dataport.org\u002Fopen-access\u002Findustrial-machines-dataset-electrical-load-disaggregation) \u003Cbr>\u003Csub>Machines\u003C\u002Fsub>               | ![Elect](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FElectrical-16a34a?style=flat-square) | Load Analysis   | Industrial    | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![IEEE](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIEEE-00629b?style=flat-square)           | IEEE     |\n| **17** | [**BACS Security**](https:\u002F\u002Fieee-dataport.org\u002Fdocuments\u002Fdataset-bundle-building-automation-and-control-systems-security-analysis#) \u003Cbr>\u003Csub>Control Systems\u003C\u002Fsub> | ![Ctrl](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FControl-4f46e5?style=flat-square)     | Automation Sec  | Security      | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-4338ca?style=flat-square)   | IEEE     |\n| **18** | [**Advanced DSP**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Femirhanai\u002Fadvanced-signal-processing-dataset-from-ai-sensors) \u003Cbr>\u003Csub>Signal Proc\u003C\u002Fsub>                       | ![DSP](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDSP-7c3aed?style=flat-square)          | AI Sensors      | Technical     | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![ML](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FML-db2777?style=flat-square)               | Kaggle   |\n| **19** | [**Wireless Comm**](https:\u002F\u002Fcatalog.data.gov\u002Fdataset\u002F?tags=wireless-communications-and-networks) \u003Cbr>\u003Csub>Communication\u003C\u002Fsub>                                     | ![Comm](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FComm-2563eb?style=flat-square)        | Network Records | Gov Data      | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)             | Data.gov |\n| **20** | [**5G Network Data**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fvinothkannaece\u002F5g-network-data) \u003Cbr>\u003Csub>Cellular\u003C\u002Fsub>                                                     | ![5G](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F5G-059669?style=flat-square)            | Perf Logs       | Mobile        | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)       | Kaggle   |\n| **21** | [**RF Signal Data**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fsuraj520\u002Frf-signal-data) \u003Cbr>\u003Csub>Antenna\u003C\u002Fsub>                                                              | ![RF](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRF-ea580c?style=flat-square)            | Signal Patterns | Technical     | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)       | Kaggle   |\n| **22** | [**Calcite VLSI**](https:\u002F\u002Fgithub.com\u002Fvlsi\u002Fcalcite-test-dataset) \u003Cbr>\u003Csub>IC Design\u003C\u002Fsub>                                                                         | ![VLSI](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVLSI-6d28d9?style=flat-square)        | Testing Data    | Design        | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)           | GitHub   |\n| **23** | [**PhysioNet Signals**](https:\u002F\u002Fphysionet.org\u002F) \u003Cbr>\u003Csub>Physiology\u003C\u002Fsub>                                                                                         | ![Med](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBioMed-dc2626?style=flat-square)       | ECG\u002FEEG         | Global        | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Archive](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FArchive-4b5563?style=flat-square)     | MIT      |\n| **24** | [**MIMIC-IV Demo**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fmontassarba\u002Fmimic-iv-clinical-database-demo-2-2) \u003Cbr>\u003Csub>Clinical\u003C\u002Fsub>                                      | ![Med](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBioMed-dc2626?style=flat-square)       | Intensive Care  | Demo Scale    | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)       | MIT      |\n| **25** | [**BraTS 2020**](https:\u002F\u002Fwww.med.upenn.edu\u002Fcbica\u002Fbrats2020\u002Fdata.html) \u003Cbr>\u003Csub>Imaging\u003C\u002Fsub>                                                                      | ![BioMed](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBioMed-dc2626?style=flat-square)    | Tumor Seg       | Medical       | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Benchmark](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBenchmark-b45309?style=flat-square) | UPenn    |\n| **26** | [**COVID Radiography**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Ftawsifurrahman\u002Fcovid19-radiography-database) \u003Cbr>\u003Csub>Radiology\u003C\u002Fsub>                                     | ![Med](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FBioMed-dc2626?style=flat-square)       | Chest X-ray     | 21k+ Images   | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)       | Kaggle   |\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n\n  # 🧠 Intelligence, Robotics & Deep Learning\n\n| Serial  | Dataset                                                                                                                                                                                  | Domain                                                                       | Field \u002F Task    | Scale        | Strength                                                                | Type                                                                            | Source    |\n| ------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | --------------- | ------------ | ----------------------------------------------------------------------- | ------------------------------------------------------------------------------- | --------- |\n| **27**  | [**NREL Solar PDS**](https:\u002F\u002Fgithub.com\u002FCharlie5DH\u002FSolar-Power-Datasets-and-Resources) \u003Cbr>\u003Csub>Energy\u003C\u002Fsub>                                                                             | ![Renew](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRenewable-fbbf24?style=flat-square)    | PV Integration  | High-res     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | NREL      |\n| **28**  | [**NREL Wind Toolkit**](https:\u002F\u002Fwww.nrel.gov\u002Fgrid\u002Fwind-toolkit.html) \u003Cbr>\u003Csub>Wind\u003C\u002Fsub>                                                                                                 | ![Renew](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRenewable-fbbf24?style=flat-square)    | Wind Power      | Continental  | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | NREL      |\n| **29**  | [**GEFCom Wind**](https:\u002F\u002Fwww.kaggle.com\u002Fcompetitions\u002FGEF2012-wind-forecasting) \u003Cbr>\u003Csub>Forecasting\u003C\u002Fsub>                                                                               | ![Renew](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRenewable-fbbf24?style=flat-square)    | Forecasting     | Multi-site   | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square)     | GEFCom    |\n| **30**  | [**Open Power System**](https:\u002F\u002Fdata.open-power-system-data.org\u002F) \u003Cbr>\u003Csub>Grid\u003C\u002Fsub>                                                                                                    | ![Power](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPower-16a34a?style=flat-square)        | Renewables      | European     | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | OPSD      |\n| **31**  | [**NASA Turbofan**](https:\u002F\u002Fti.arc.nasa.gov\u002Ftech\u002Fdash\u002Fgroups\u002Fpcoe\u002Fprognostic-data-repository\u002F) \u003Cbr>\u003Csub>Mechanical\u003C\u002Fsub>                                                                 | ![Mech](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMechanical-4b5563?style=flat-square)    | Degradation     | Predictive   | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![NASA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNASA-e03c31?style=flat-square)             | NASA      |\n| **32**  | [**Engine Vibration**](https:\u002F\u002Fgithub.com\u002FCharlie5DH\u002FPredictiveMaintenance-and-Vibration-Resources) \u003Cbr>\u003Csub>Sound\u003C\u002Fsub>                                                                 | ![Mech](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMechanical-4b5563?style=flat-square)    | Maintenance     | Sensor Data  | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | GitHub    |\n| **33**  | [**Structural Health**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fziya07\u002Fbuilding-structural-health-sensor-dataset) \u003Cbr>\u003Csub>Civil\u003C\u002Fsub>                                                           | ![Civil](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCivil-b45309?style=flat-square)        | Monitoring      | Building     | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Kaggle    |\n| **34**  | [**Awesome Robotics**](https:\u002F\u002Fgithub.com\u002Fmint-lab\u002Fawesome-robotics-datasets) \u003Cbr>\u003Csub>Robotics\u003C\u002Fsub>                                                                                    | ![Robo](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRobotics-e11d48?style=flat-square)      | Benchmarks      | Curated      | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Resource](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResource-22863a?style=flat-square)     | GitHub    |\n| **35**  | [**KITTI Vision**](http:\u002F\u002Fwww.cvlibs.net\u002Fdatasets\u002Fkitti\u002F) \u003Cbr>\u003Csub>Autonomous\u003C\u002Fsub>                                                                                                      | ![AV](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAutonomous-2563eb?style=flat-square)      | Vision Bench    | Driving      | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-4338ca?style=flat-square)     | CVLibs    |\n| **36**  | [**Waymo Open**](https:\u002F\u002Fwaymo.com\u002Fopen\u002F) \u003Cbr>\u003Csub>Perception\u003C\u002Fsub>                                                                                                                      | ![AV](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAutonomous-2563eb?style=flat-square)      | Motion\u002FDriving  | Massive      | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Corporate](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCorporate-000000?style=flat-square)   | Waymo     |\n| **37**  | [**ApolloScape**](http:\u002F\u002Fapolloscape.auto\u002F) \u003Cbr>\u003Csub>Scene Parsing\u003C\u002Fsub>                                                                                                                 | ![AV](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAutonomous-2563eb?style=flat-square)      | Video Parsing   | High Res     | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-0D5FA6?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | Apollo    |\n| **38**  | [**ASHRAE Energy**](https:\u002F\u002Fwww.kaggle.com\u002Fc\u002Fashrae-energy-prediction) \u003Cbr>\u003Csub>Civil\u003C\u002Fsub>                                                                                              | ![Civil](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCivil-b45309?style=flat-square)        | Prediction      | Building     | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square)     | Kaggle    |\n| **39**  | [**Pavia University**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fsyamkakarla\u002Fpavia-university-hsi) \u003Cbr>\u003Csub>Remote Sensing\u003C\u002Fsub>                                                                   | ![RS](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRS-059669?style=flat-square)              | Hyperspectral   | Aerial       | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square)     | Pavia     |\n| **40**  | [**Concrete Strength**](https:\u002F\u002Farchive.ics.uci.edu\u002Fml\u002Fdatasets\u002FConcrete+Compressive+Strength) \u003Cbr>\u003Csub>Materials\u003C\u002Fsub>                                                                  | ![Civil](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCivil-b45309?style=flat-square)        | Compression     | Industrial   | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![UCI](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FUCI-ea580c?style=flat-square)               | UCI       |\n| **41**  | [**QM9 Molecules**](https:\u002F\u002Fquantum-machine.org\u002Fdatasets\u002F) \u003Cbr>\u003Csub>Catalysis\u003C\u002Fsub>                                                                                                      | ![Chem](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FChemical-0d9488?style=flat-square)      | Molecular       | Quantum      | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![Quantum](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FQuantum-7c3aed?style=flat-square)       | QM Org    |\n| **42**  | [**DREAM Simulation**](https:\u002F\u002Fzenodo.org\u002Frecords\u002F3735364) \u003Cbr>\u003Csub>Chemical\u003C\u002Fsub>                                                                                                       | ![Chem](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FChemical-0d9488?style=flat-square)      | Process Sim     | Research     | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | Zenodo    |\n| **43**  | [**Heart Disease**](https:\u002F\u002Farchive.ics.uci.edu\u002Fdataset\u002F45\u002Fheart+disease) \u003Cbr>\u003Csub>Industrial Chem\u003C\u002Fsub>                                                                                 | ![Chem](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FChemical-0d9488?style=flat-square)      | Sensor Data     | Medical      | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![UCI](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FUCI-ea580c?style=flat-square)               | UCI       |\n| **44**  | [**PSE Datasets**](https:\u002F\u002Fdata.world\u002Fbriannielsen\u002Fprocess-systems-engineering) \u003Cbr>\u003Csub>Process Eng\u003C\u002Fsub>                                                                               | ![PSE](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPSE-4f46e5?style=flat-square)            | Engineering     | Systems      | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | DataWorld |\n| **45**  | [**Airfoil Noise**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Ffedesoriano\u002Fairfoil-selfnoise-dataset) \u003Cbr>\u003Csub>NASA Aero\u003C\u002Fsub>                                                                      | ![Aero](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAero-2563eb?style=flat-square)          | Self-Noise      | Technical    | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | NASA      |\n| **46**  | [**Flight Delay**](https:\u002F\u002Fwww.transtats.bts.gov\u002FOT_Delay\u002F) \u003Cbr>\u003Csub>Aviation\u003C\u002Fsub>                                                                                                      | ![Aero](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAero-2563eb?style=flat-square)          | Delay Stats     | National     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | BTS       |\n| **47**  | [**NASA C-MAPSS**](https:\u002F\u002Fgithub.com\u002Fkpeters\u002Fexploring-nasas-turbofan-dataset) \u003Cbr>\u003Csub>Engine\u003C\u002Fsub>                                                                                    | ![Aero](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAero-2563eb?style=flat-square)          | Degradation     | Simulation   | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![NASA](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNASA-e03c31?style=flat-square)             | NASA      |\n| **48**  | [**OpenAeroStruct**](https:\u002F\u002Fgithub.com\u002Fmdolab\u002FOpenAeroStruct) \u003Cbr>\u003Csub>Structural\u003C\u002Fsub>                                                                                                 | ![Aero](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAero-2563eb?style=flat-square)          | Optimization    | Numerical    | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![GitHub](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGitHub-000000?style=flat-square)         | MDO Lab   |\n| **49**  | [**ERA5 Atmospheric**](https:\u002F\u002Fcds.climate.copernicus.eu\u002Fdatasets) \u003Cbr>\u003Csub>Env Reanalysis\u003C\u002Fsub>                                                                                         | ![Env](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEnv-0891b2?style=flat-square)            | Global Data     | Multi-PB     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-22863a?style=flat-square)     | CDS       |\n| **50**  | [**Smart Manu IoT**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Fziya07\u002Fsmart-manufacturing-iot-cloud-monitoring-dataset) \u003Cbr>\u003Csub>Industrial\u003C\u002Fsub>                                                  | ![Manu](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FManu-4b5563?style=flat-square)          | Failure Det     | IoT Cloud    | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Kaggle    |\n| **51**  | [**SECOM Data**](https:\u002F\u002Farchive.ics.uci.edu\u002Fml\u002Fdatasets\u002FSECOM) \u003Cbr>\u003Csub>Semiconductor\u003C\u002Fsub>                                                                                             | ![Manu](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FManu-4b5563?style=flat-square)          | Monitoring      | Production   | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![UCI](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FUCI-ea580c?style=flat-square)               | UCI       |\n| **52**  | [**Tennessee Eastman**](https:\u002F\u002Fgithub.com\u002Fjonathanwvd\u002Fawesome-industrial-datasets\u002Fblob\u002Fmaster\u002Fmarkdown\u002Ftennessee_eastman_process_simulation_dataset.md) \u003Cbr>\u003Csub>Chemical Process\u003C\u002Fsub> | ![Manu](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FManu-4b5563?style=flat-square)          | Process Sim     | Benchmark    | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![Academic](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAcademic-b45309?style=flat-square)     | GitHub    |\n| **53**  | [**Open Jobs BLS**](https:\u002F\u002Fwww.bls.gov\u002Fdata\u002F) \u003Cbr>\u003Csub>Workforce\u003C\u002Fsub>                                                                                                                  | ![Econ](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEcon-16a34a?style=flat-square)          | Job Data        | National     | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | BLS       |\n| **54**  | [**Assembly Line**](https:\u002F\u002Funiverse.roboflow.com\u002Fwd-rohcm\u002Fdataset-s7uii) \u003Cbr>\u003Csub>Sensors\u003C\u002Fsub>                                                                                         | ![Manu](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FManu-4b5563?style=flat-square)          | Sensor Data     | Image\u002FVision | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | Roboflow  |\n| **55**  | [**Materials NIST**](https:\u002F\u002Fgithub.com\u002Fsedaoturak\u002Fdata-resources-for-materials-science) \u003Cbr>\u003Csub>Metallurgical\u003C\u002Fsub>                                                                    | ![Metal](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMetal-059669?style=flat-square)        | Material Repo   | Registry     | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | NIST      |\n| **56**  | [**Materials Project**](https:\u002F\u002Fmaterialsproject.org\u002F) \u003Cbr>\u003Csub>Crystallography\u003C\u002Fsub>                                                                                                    | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | Properties      | 100k+ Struct | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Open](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FOpen-22863a?style=flat-square)             | LBNL      |\n| **57**  | [**OQMD Database**](https:\u002F\u002Fcolab.research.google.com\u002Fgithub\u002FTony-Y\u002Foqmd-v1.2-dataset-for-cgnn\u002Fblob\u002Fmain\u002FOQMD_v1_2_dataset_for_CGNN.ipynb) \u003Cbr>\u003Csub>Quantum Mat\u003C\u002Fsub>                    | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | CGNN Training   | Quantum      | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Notebook](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNotebook-7c3aed?style=flat-square)     | TonyY     |\n| **58**  | [**Materials Project DB**](https:\u002F\u002Fmaterialsproject.org\u002F) \u003Cbr>\u003Csub>Eng Materials\u003C\u002Fsub>                                                                                                   | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | Engineering     | Scientific   | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![Research](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FResearch-4338ca?style=flat-square)     | Berkeley  |\n| **59**  | [**Thermo-Calc NIST**](https:\u002F\u002Fwww.nist.gov\u002Fprograms\u002Fprojects\u002Fthermo-calc-data) \u003Cbr>\u003Csub>Eng Materials\u003C\u002Fsub>                                                                             | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | Thermodynamic   | Precise Data | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | NIST      |\n| **60**  | [**Citrine Materials**](https:\u002F\u002Fcitrine.io\u002Fmedia-post\u002Fdata-highlight-materials-project-dataset\u002F) \u003Cbr>\u003Csub>Citrine Data\u003C\u002Fsub>                                                             | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | Highlight Data  | Enterprise   | ![7\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F7%2F10-e67e22?style=flat-square)   | ![Industry](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIndustry-4b5563?style=flat-square)     | Citrine   |\n| **61**  | [**Jarvis DFT**](https:\u002F\u002Fjarvis.nist.gov\u002F) \u003Cbr>\u003Csub>MatSci Database\u003C\u002Fsub>                                                                                                                | ![MatSci](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMatSci-0d9488?style=flat-square)      | DFT Database    | High Quality | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![Gov](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGov-22863a?style=flat-square)               | NIST      |\n| **62**  | [**Human Activity HAR**](https:\u002F\u002Farchive.ics.uci.edu\u002Fml\u002Fdatasets\u002FHuman+Activity+Recognition+Using+Smartphones) \u003Cbr>\u003Csub>Mechatronics\u003C\u002Fsub>                                               | ![Mecha](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMechatronics-ea580c?style=flat-square) | HAR Patterns    | Sensor Logs  | ![10\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F10%2F10-006400?style=flat-square) | ![UCI](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FUCI-ea580c?style=flat-square)               | UCI       |\n| **63**  | [**Robotic Grasping**](https:\u002F\u002Fwww.kaggle.com\u002Fdatasets\u002Foneoneliu\u002Fcornell-grasp) \u003Cbr>\u003Csub>Grasping\u003C\u002Fsub>                                                                                  | ![Robo](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRobotics-e11d48?style=flat-square)      | Cornell Bench   | Imaging      | ![8\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F8%2F10-2e7d32?style=flat-square)   | ![Kaggle](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FKaggle-0D5FA6?style=flat-square)         | Cornell   |\n| **64**  | [**OpenAI Robogym**](https:\u002F\u002Fgithub.com\u002Fopenai\u002Frobogym) \u003Cbr>\u003Csub>Environments\u003C\u002Fsub>                                                                                                      | ![Robo](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FRobotics-e11d48?style=flat-square)      | RL Gym          | Training     | ![9\u002F10](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F9%2F10-006400?style=flat-square)   | ![GitHub](ht","Awesome-Datasets-Hub 是一个为大型语言模型（LLMs）精心挑选的数据集集合，涵盖了医学AI、自然语言处理、多模态学习、指令调优、推理、代码生成及评估基准等多个领域。项目的核心功能在于提供高质量且多样化的数据集，支持不同任务需求，如医疗问答、生物医学信息抽取等，并对每个数据集的规模、强度、语言和许可进行了详细标注。这些资源非常适合从事机器学习特别是深度神经网络研究与应用的专业人士使用，在开发或优化针对特定任务的语言模型时尤为有用。",2,"2026-06-11 03:54:21","CREATED_QUERY"]