Deep Learning is an artificial neural network composed of many layers.
There are 59,724 repositories under deep-learning topic.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Deep Learning for humans
List of Computer Science courses with video lectures.
Stable Diffusion web UI
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
100 Days of ML Coding
Clone a voice in 5 seconds to generate arbitrary speech in real-time
DeepFaceLab is the leading software for creating deepfakes.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Learn how to responsibly develop, deploy and maintain production machine learning applications.
Pure Javascript OCR for more than 100 Languages 📖🎉🖥
🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
A complete daily plan for studying to become a machine learning engineer.
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
PyTorch Tutorial for Deep Learning Researchers
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
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.
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
Roadmap to becoming an Artificial Intelligence Expert in 2022
The most cited deep learning papers
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Deep learning framework to train, deploy, and ship AI products Lightning fast.
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.
Visualizer for neural network, deep learning, and machine learning models