microsoft/ai-agents-for-beginners
18 Lessons to Get Started Building AI Agents
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18 Lessons to Get Started Building AI Agents
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
One has no future if one couldn't teach themself.
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
MiniCPM5: SOTA on-device LLMs, small yet powerful.
Examples and guides for using the OpenAI API
📚 《Deep Agents 实战》—— LangChain 官方大使出品,基于 LangChain / LangGraph 生态,从零构建生产级 AI Agent 的完整指南
10 Weeks, 20 Lessons, Data Science for All!
Learn ML engineering for free in 4 months! Register here 👇🏼
FinRL®: Financial Reinforcement Learning. 🔥
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
The fastai deep learning library
A game theoretic approach to explain the output of any machine learning model.
A collection of guides and examples for the Gemma open models from Google.