Crack LeetCode, not only how, but also why.
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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
📜 33 JavaScript concepts every developer should know.
🧠 Train a 64M-parameter LLM from scratch in just 2h!
Translated"Code Random Thoughts" (代码随想录) LeetCode problem-solving guide: the order for working through 200 classic problems, with 600,000 characters of detailed illustrated explanations, video analysis of difficult points, and over 50 mind maps. Supports multiple language versions including C++, Java, Python, Go, and JavaScript, so learning algorithms is never confusing again! 🔥🔥 Come take a look, and you will wish you had met it sooner! 🚀
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
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
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
🤪 A list of funny and tricky JavaScript examples
- javascript
- specification
- handbook
- notes
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.
:snowman: Possibly the smallest compiler ever
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
Translated:star2: Wiki of OI / ICPC for everyone. (An online walkthrough for a certain large game, containing cool arithmetic magic)
- oi
- oi-handbook
- data-structures
- algorithms
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
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
💻 Vibe Coding 101｜Your First Course For AI Product Builders.
- ai
- course
- vibe-coding
- coding
🎮 A step-by-step guide to implementing SSAO, depth of field, lighting, normal mapping, and more for your 3D game.
Setup instructions for Le Wagon's students on their first day of AI Software Development Bootcamp
- setup
- ruby
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
Examples and guides for using the Gemini API
Architecture decision record (ADR) examples for software planning, IT leadership, and template documentation
- adr
- documentation
- teamwork
- architecture-decision-record