awesome-ai-ml-dl
github.com/neomatrix369/awesome-ai-ml-dl โAwesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
1.7k
GitHub Stars
1.3k
Curated Resources
95
Categories
17 hours ago
Last Refreshed
Learning ResourcesTools & Infrastructure๐ GeneralSupervisedUnsupervisedActive LearningNeural NetworksGenerative Adversarial Network (GAN)Genetic AlgorithmsRNNComputer VisionData ScienceMachine LearningRecommendation Systems๐ Programming in Rโ More...Data๐ผ Business / General / Semi-technical๐ณ Classifier / decision treesCorrelated Cross OccurrenceJava projects / related technologies๐ง Neural NetworksRecommendation systems / Collaborative Filtering (CF)๐ Data Science๐ค Machine Learning๐ ๏ธ Tools & Libraries, Other ResourcesJava Specification RequestsHow-to / Deploy / DevOps / ServerlessMiscInfrastructure & CloudMLOps & DeploymentLarge Language Models (LLMs)NotebooksNLPTools & FrameworksArtificial IntelligenceAutomationEthics / altruistic motives๐น Golang๐ MLOps & Deployment๐ ๏ธ Tools & Frameworks๐ง NLPโ๏ธ Infrastructure & CloudTools, Libraries, Packages, FrameworksImplementations and examplesPosts, articles, papers and other resourcesHow-tos, and why?Books and other resources๐ Algorithms๐ Cambridge Spark๐ Datacamp๐ง Dataiku๐ผ๏ธ Computer Vision๐ป Intel๐ง Natural Language Processing (NLP)๐ Python: Best practices๐งช Python: Testing๐ Statistics๐ฆ Misc๐ Dataโจ Generative AIGeneralCoding challengesResources๐ Virgili0๐ Notebooks๐๏ธ Large Language Models (LLMs)๐ฐ Media sources๐ Useful blogs to read๐ Course providers๐ง Primary tools to analyse data๐ป IDEs๐ Hosted Notebook products๐ป Programming languages๐ Data visualization libraries or tools๐ค Machine learning Algorithms๐ ๏ธ Machine learning frameworks๐ฆ Machine learning products๐ Big data / analytics productsโ๏ธ Cloud computing platformsโ๏ธ Cloud computing products๐ Automated pipelines๐ค Automated machine learning tools (or partial AutoML tools)๐ Tools to help manage machine learning experiments๐ Publicly share or deploy your data analysis or machine learning applications๐๏ธ Relational database products๐ Business intelligence tools๐งฐ Other ToolsOfficial Documentation {#official-documentation}MCP Server Catalogs {#mcp-server-catalogs}Configuration GuidesForums and Community Support {#forums-and-community-support}AI AgentsMathematics๐ฒ Probability and Probabilistic programming
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me deep learning resources from awesome-ai-ml-dl"
Installation instructions โWhat's inside
Books and other resources
- "๐ผ ๐๐ค๐ค๐ ๐ซ๐๐จ๐ช๐๐ก๐๐ฏ๐๐ฉ๐๐ค๐ฃ ๐๐จ ๐ฃ๐ค๐ฉ ๐๐ช๐จ๐ฉ ๐ ๐ฅ๐๐๐ฉ๐ช๐ง๐ ๐๐ฉ ๐๐จ ๐ ๐จ๐ฉ๐ค๐ง๐ฎ. ๐๐๐ ๐จ๐ฉ๐ค๐ง๐ฎ ๐ค๐ ๐ค๐ฃ๐โ๐จ ๐๐ค๐ช๐ง๐ฃ๐๐ฎ ๐๐ฃ ๐ฉ๐๐ ๐๐๐ฉ๐."
- 1
- Alan Rutter
- An Infographic of โData Science Landscapeโ
๐ Statistics
- ๐ฆ ๐ฆ๐๐ฎ๐๐ถ๐๐๐ถ๐ฐ๐ ๐ถ๐ ๐ฎ๐ป ๐ฒ๐๐๐ฒ๐ป๐๐ถ๐ฎ๐น ๐ฝ๐ฎ๐ฟ๐ ๐ณ๐ผ๐ฟ ๐๐ป๐ฑ๐ฒ๐ฟ๐๐๐ฎ๐ป๐ฑ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐ฑ๐ฎ๐๐ฎ, ๐๐ผ ๐ฏ๐ฒ๐ณ๐ผ๐ฟ๐ฒ ๐ฑ๐ฒ๐ฒ๐ฝ ๐ฑ๐ถ๐๐ฒ ๐ถ๐ป๐๐ผ ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐น๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ถ๐๐ ๐ด๐ผ๐ผ๐ฑ ๐ฝ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ ๐๐ผ ๐๐ป๐ฑ๐ฒ๐ฟ๐๐๐ฎ๐ป๐ฑ ๐๐ต๐ฒ ๐ณ๐๐ป๐ฑ๐ฎ๐บ๐ฒ๐ป๐๐ฎ๐น ๐ผ๐ณ ๐ฆ๐๐ฎ๐๐ถ๐๐๐ถ๐ฐ๐ ๐ฎ๐ป๐ฑ ๐๐ต๐ฒ๐ฟ๐ฒ ๐ถ๐'๐ ๐๐๐ฒ๐ฑ.
- 32 Type of Statisical Distribution, by Rasmus Baath
- 5 Lesson 5 Measures Of Skewness And Kurtosis
- An Introduction To Statistical Learning with Applications in R
Data Science
- ๐๐ฏ๐๐ซ๐ฒ ๐๐๐ญ๐ ๐ฌ๐๐ข๐๐ง๐ญ๐ข๐ฌ๐ญ ๐ฌ๐ก๐จ๐ฎ๐ฅ๐ ๐ก๐๐ฏ๐ ๐ค๐ง๐จ๐ฐ๐ฅ๐๐๐ ๐ ๐จ๐ ๐ญ๐ก๐ข๐ฌ ๐๐จ๐ง๐๐๐ฉ๐ญ
- 10 Books Data Scientists Should Read During Lockdown
- 20 short tutorials all data scientists should read (and practice)
- ๐50 Days of Machine Learning๐
- 50 external machine learning / data science resources and articles
- 50 most popular Python libraries and frameworks used in data science
๐ค Machine Learning
๐ง NLP
โจ Generative AI
Tools, Libraries, Packages, Frameworks
Showing a sample of 1.3k resources. View the full list on GitHub โ