ml-road
Machine Learning and Agentic AI Resources, Practice and Research.
yanshengjia/ml-road is ranked 4,637 with 4,961 stars.
yanshengjia/ml-road is ranked 4,637 among these 8 peers; nibzard/awesome-agentic-patterns is ranked 4,629.
| Name | Rank | Metrics |
|---|---|---|
| ombharatiya/FAANG-Coding-Interview-Questions | 4,555 |
|
| xlite-dev/Awesome-LLM-Inference | 4,591 |
|
| filipecalegario/awesome-vibe-coding | 4,602 |
|
| nibzard/awesome-agentic-patterns | 4,629 |
|
| alvinreal/awesome-opensource-ai | 4,646 |
|
| LantaoYu/MARL-Papers | 4,647 |
|
| r0f1/datascience | 4,668 |
|
| GT-RIPL/Awesome-LLM-Robotics | 4,682 |
|
| Parameter | Value |
|---|---|
| Language | Python |
| Category | Lists |
| Subcategory | Tool collections |
| Stars | 4,961 |
| Forks | 1,722 |
| Contributors | 1 |
| Created date | 2017-10-31 |
| Updated date | 2026-10-16 |
| Stars in 1 day | 1 |
| Stars in 7 days | 7 |
| Rank | 4,637 |
| Previous rank | 7,618 |
| Rank change | 2,981 |
| 7-day stars rank | 4,622 |
| Previous 7-day stars rank | 4,986 |
| 7-day stars rank change | 364 |
| Total stars rank | 2,827 |
| Previous total stars rank | 2,822 |
| Total stars rank change | -5 |
| Country | USA |
Machine Learning Road Machine Learning and Agentic AI Resources, Practice and Research. Disclamier The resources in this repo are only for educational purpose. Do not use resources in this repo for any form of commercial purpose. If the author of ebook found your intelligence proprietary violated because of contents in this repo, please contact me and I will remove relevant stuff ASAP. Witten, Eibe Frank | [[PDF]]( | Data Mining | | Artificial Intelligence: A Modern Approach | Sturart J. Russell, Peter Norvig | [[PDF]]( | AI
| | Machine Learning: A Probabilistic Perspective | Kevin P. Murphy | [[PDF]]( | Machine Learning | | Natural Language Processing with Python | Stven Bird, Ewan Klein, Edward Loper | [[PDF]]( | NLP | | Getting Started with Tensorflow | Giancarlo Zaccone | [[PDF]]( | Tensorflow | | Hands-On Machine Learning with Scikit-Learn and TensorFlow | Aurélien Géron | [[PDF]]( | Machine Learning | | Deep Learning with Python | François Chollet | [[PDF]]( | Deep Learning | | Probabilistic Graphical Models: Principles and Techniques | Daphne Koller, Nir Friedman | [[PDF]]( | Probabilistic Graphical Model | | Speech and Language Processing | Dan Jurafsky, James H
. AI]]( | Agentic AI Fundamentals | | LangChain for LLM Application Development | Course | Harrison Chase, Andrew Ng | [[DeepLearning. AI]]( | LLM Applications, Agents | | Building Systems with the ChatGPT API | Course | Isa Fulford, Andrew Ng | [[DeepLearning. AI]]( | LLM Applications, Agents | | Strands Agents | SDK | Strands | [[Homepage]]( | Multi-Agent Systems | | AI Agents in LangGraph | Course | Harrison Chase, Rotem Weiss | [[DeepLearning. AI]]( | Agent Frameworks | | ChatGPT Prompt Engineering for Developers | Course | Isa Fulford, Andrew Ng | [[DeepLearning. AI]]( | Prompt Engineering | | ReAct: Synergizing Reasoning and Acting in Language Models | Paper | Yao
et al. | [[arXiv]]( | Reasoning, Planning | | Toolformer: Language Models Can Teach Themselves to Use Tools | Paper | Schick et al. | [[arXiv]]( | Tool Use | | Deep Dive into LLMs like ChatGPT | Course | Andrej Karpathy | [[YouTube]]( | LLM Fundamentals | | Build your first Agentic AI app step-by-step with Strands Agents & MCP | Course | AWS | [[YouTube]]( | Agentic AI Applications | | Building Effective AI Agents | Blog | Anthropic | [[Anthropic]]( | Agent Design, Best Practices | | How We Built Our Multi-Agent Research System | Blog | Anthropic | [[Anthropic]]( | Multi-Agent Systems, Architecture |
How many stars and forks are recorded?
yanshengjia/ml-road has 4,961 stars and 1,722 forks.
What is the repository rank?
yanshengjia/ml-road is ranked 4,637.
What language and category are recorded?
yanshengjia/ml-road has 4,961 stars, uses Python and belongs to Lists.
Which repository is closest in rank?
yanshengjia/ml-road is compared with nibzard/awesome-agentic-patterns, ranked 4,629 with 5,035 stars.