This is the latest advanced react patterns workshop
- kcd-edu
- react-patterns
- workshop
- react
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This is the latest advanced react patterns workshop
Follow along with my AI Agents Masterclass videos! All of the code I create and use in this series on YouTube will be here for you to use and even build on top of!
A Code-First Introduction to NLP course
免费学代码系列:小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Companion repo for complete Docker course
Learn Mini Program
Learn how to automate faceless short-form + long-form video content and dominate YouTube, TikTok, Facebook & Instagram on autopilot — from idea → script → video → scheduled posts.
Five lessons, learn how to really apply AI to your .NET Applications
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
Student version of Assignment 1 for Stanford CS336 - Language Modeling From Scratch
A no-fluff and highly practical masterclass that reignites engineering curiosity and helps SDE-2, SDE-3, and above become great at designing, implementing, and shipping scalable, fault-tolerant, and highly available systems at the workplace.
Repositório responsável pelo Curso de TypeScript - Zero to Hero
NMA Computational Neuroscience course
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.
✔️李沐 【动手学深度学习】课程学习笔记:使用pycharm编程,基于pytorch框架实现。
Starter files, final projects, and FAQ for my HTML + CSS course
Free hands-on digital forensics labs for students and faculty
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Devops Tutorial for Beginners - Learn Docker, Kubernetes, Terraform, Ansible, Jenkins and Azure Devops
Material do Curso de HTML5 e CSS3 do Curso em Vídeo
📚 《Deep Agents 实战》—— LangChain 官方大使出品,基于 LangChain / LangGraph 生态,从零构建生产级 AI Agent 的完整指南
TranslatedCovers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning