Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
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List of Computer Science courses with video lectures.
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Learn AI Engineering! Learn it. Build it. Ship it for others.
12 Weeks, 24 Lessons, AI for All!
🧑🏫 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
Learn how to develop, deploy and iterate on production-grade ML applications.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
500 AI Machine learning Deep learning Computer vision NLP Projects with code
- awesome
- machine-learning
- deep-learning
- machine-learning-projects
深度学习经典、新论文逐段精读
- deep-learning
- paper
- reading-list
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
- machine-learning
- deep-learning
- deep-reinforcement-learning
- machine-learning-from-scratch
PyTorch Tutorial for Deep Learning Researchers
- deep-learning
- pytorch-tutorial
- neural-networks
- pytorch
Roadmap to becoming an Artificial Intelligence Expert in 2022
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
- applied-machine-learning
- production
- applied-data-science
- machine-learning
:memo: An awesome Data Science repository to learn and apply for real world problems.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
- artificial-intelligence
- cloud-ml
- computer-systems
- courseware
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.
A curated list of awesome Deep Learning tutorials, projects and communities.
A complete daily plan for studying to become a machine learning engineer.
- machine-learning
- deep-learning
- artificial-intelligence
- software-engineer
deep learning for image processing including classification and object-detection etc.
- pytorch
- tensorflow2
- classification
- object-detection