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🧑🏫 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, ... 🧠
Best Practices on Recommendation Systems
A resource for learning about Machine learning & Deep Learning
The most comprehensive Claude Code guide: agentic workflows, hooks, skills, MCP servers, quizzes, and production-ready templates. 430K+ lines.
TranslatedThis is a step-by-step guide to getting started with AI/LLM large models, including tutorials and demo code, taking you from APIs to local large model deployment and fine-tuning. The code files come with Kaggle or Colab online versions, so you can learn even without a graphics card. The project also has a small code playground 🎡 where you can try out some interesting AI scripts. It also includes complete Chinese mirror assignments for Hung-Yi Lee's (HUNG-YI LEE) 2024 Introduction to Generative AI course.
Examples and tutorials to help developers build AI systems
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.