aselshall/ESM_Tutorial
Using Earth System Models: A Tutorial
GitHub repository with 5 stars and 7 forks.
Language: Jupyter Notebook
Using Earth System Models: A Tutorial
GitHub repository with 5 stars and 7 forks.
Language: Jupyter Notebook
2026-07-16: 5 stars and 7 forks.
18 Lessons to Get Started Building AI Agents
GitHub repository with 69,488 stars and 23,048 forks.
Trending score: 4.11; stars gained: +83; forks gained: +31.
Language: Jupyter Notebook
Topics: agentic-ai, agentic-framework, agentic-rag, ai-agents, ai-agents-framework, autogen
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
GitHub repository with 19,904 stars and 5,411 forks.
Trending score: 3.81; stars gained: +79; forks gained: +7.
Language: Jupyter Notebook
Topics: algorithmic-trading, artificial-intelligence, backtesting, data-science, deep-learning, finance
21 Lessons, Get Started Building with Generative AI
GitHub repository with 113,035 stars and 60,716 forks.
Trending score: 3.78; stars gained: +63; forks gained: +34.
Language: Jupyter Notebook
Topics: ai, azure, chatgpt, dall-e, generative-ai, generativeai
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
GitHub repository with 88,186 stars and 21,508 forks.
Trending score: 3.60; stars gained: +32; forks gained: +17.
Language: Jupyter Notebook
LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词(Structured Prompt)提出者 📌 元提示词(Meta-Prompt)发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树
GitHub repository with 12,350 stars and 935 forks.
Trending score: 3.17; stars gained: +83; forks gained: +3.
Language: Jupyter Notebook
Topics: chatgpt, claude, deeplearning, doubao, framework, gemini
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
GitHub repository with 36,529 stars and 6,056 forks.
Trending score: 3.09; stars gained: +7; forks gained: +2.
Language: Jupyter Notebook
Topics: agents, ai, llms, machine-learning, mcp, rag
18 Lessons to Get Started Building AI Agents
GitHub repository with 69,488 stars and 23,048 forks.
Trending score: 4.11; stars gained: +83; forks gained: +31.
Language: Jupyter Notebook
Topics: agentic-ai, agentic-framework, agentic-rag, ai-agents, ai-agents-framework, autogen
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
GitHub repository with 19,904 stars and 5,411 forks.
Trending score: 3.81; stars gained: +79; forks gained: +7.
Language: Jupyter Notebook
Topics: algorithmic-trading, artificial-intelligence, backtesting, data-science, deep-learning, finance
21 Lessons, Get Started Building with Generative AI
GitHub repository with 113,035 stars and 60,716 forks.
Trending score: 3.78; stars gained: +63; forks gained: +34.
Language: Jupyter Notebook
Topics: ai, azure, chatgpt, dall-e, generative-ai, generativeai
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
GitHub repository with 88,186 stars and 21,508 forks.
Trending score: 3.60; stars gained: +32; forks gained: +17.
Language: Jupyter Notebook
LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词(Structured Prompt)提出者 📌 元提示词(Meta-Prompt)发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树
GitHub repository with 12,350 stars and 935 forks.
Trending score: 3.17; stars gained: +83; forks gained: +3.
Language: Jupyter Notebook
Topics: chatgpt, claude, deeplearning, doubao, framework, gemini
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
GitHub repository with 36,529 stars and 6,056 forks.
Trending score: 3.09; stars gained: +7; forks gained: +2.
Language: Jupyter Notebook
Topics: agents, ai, llms, machine-learning, mcp, rag