Crack LeetCode, not only how, but also why.
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Clean Code concepts adapted for JavaScript
- javascript
- principles
- composition
- inheritance
🐙 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
Examples and guides for using the OpenAI API
🧑🏫 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
TranslatedDive into LLMs: a series of hands-on programming tutorials
TranslatedBypass the Great Firewall - scientific internet access
- ssr
- v2ray
- shadowsocks
- fanqiang
Bootstrap Kubernetes the hard way. No scripts.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
🤪 A list of funny and tricky JavaScript examples
- javascript
- specification
- handbook
- notes
Getting Started with Spring Boot 3:
What the f*ck Python? 😱
- python
- wats
- snippets
- wtf
Translated📚 Building large models from scratch
An interactive git visualization and tutorial. Aspiring students of git can use this app to educate and challenge themselves towards mastery of git!
Translated"开源大模型食用指南" (Open-Source Large Model Usage Guide): a tutorial tailor-made for Chinese users on quickly fine-tuning (full-parameter/LoRA) and deploying domestic and international open-source large language models (LLM) and multimodal large models (MLLM) in a Linux environment
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
TranslatedThis project aims to share the technical principles of large models and practical experience (large model engineering, large model application deployment).
- llm
- llm-inference
- llm-serving
- llm-training
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
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)