Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
- agent
- claude-code
- teaching
- agent-development
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🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
- deep-learning
- deep-learning-tutorial
- pytorch
- gan
100 Days of ML Coding
- machine-learning
- machine-learning-algorithms
- infographics
- tutorial
30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Learn regex the easy way
- regex
- regular-expression
- learn-regex
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
TranslatedAiLearning: Data Analysis + Machine Learning in Action + Linear Algebra + PyTorch + NLTK + TF2
- fp-growth
- apriori
- mahchine-leaning
- naivebayes
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
🤪 A list of funny and tricky JavaScript examples
- javascript
- specification
- handbook
- notes
An interactive git visualization and tutorial. Aspiring students of git can use this app to educate and challenge themselves towards mastery of git!
PyTorch Tutorial for Deep Learning Researchers
- deep-learning
- pytorch-tutorial
- neural-networks
- pytorch
A playbook for systematically maximizing the performance of deep learning models.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
TranslatedLearn step by step: Spring Boot, Spring Boot & Shiro, Spring Batch, Spring Cloud, Spring Cloud Alibaba, Spring Security & Spring Security OAuth2. Source code for the blog's Spring series: https://mrbird.cc
- spring-boot
- springboot
- learning
- shiro
30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
- challenge
- javascript
- js
- react
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
TranslatedA Python web scraping tutorial series, learning Python web scraping from 0 to 1, including browser packet capture and mobile APP packet capture with tools such as fiddler and mitmproxy, the use of the various modules involved in web scraping, such as requests, beautifulSoup, selenium, appium, scrapy, etc., as well as IP proxies, CAPTCHA recognition, using Mysql and MongoDB databases with Python, multi-threaded and multi-process scraping, reverse engineering and cracking of CSS scraping encryption, JS scraping reverse engineering, distributed scraping, practical scraping project examples, etc.
- python3
- python-script
- python-spider
TranslatedProgrammer Yupi's (程序员鱼皮) complete AI resource collection + zero-basics Vibe Coding tutorial. Shares step-by-step OpenClaw tutorials, ways to use large models (DeepSeek / GPT / Gemini / Claude / GLM), the latest AI news, a complete collection of Prompts, an AI knowledge encyclopedia (Agent Skills / RAG / MCP / A2A), AI programming tutorials (Harness Engineering), guides to using AI tools (Cursor / Claude Code / TRAE / Codex / Copilot), AI development framework tutorials (Spring AI / LangChain), and a guide to monetizing AI products, helping you quickly master AI technology and stay at the forefront of the times. This project is the open-source documentation aiguide, which has been upgraded to the Yupi AI Navigation website (鱼皮 AI 导航网站)
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
:mortar_board: All things Vim!