Popular GitHub Repositories for Vision Science

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

《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。

Deep Learning for humans

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

12 Weeks, 24 Lessons, AI for All!

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Caffe: a fast open framework for deep learning.

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

We write your reusable computer vision tools. ?

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

? Industrial-strength Natural Language Processing (NLP) in Python

OpenMMLab Detection Toolbox and Benchmark

Cross-platform, customizable ML solutions for live and streaming media.

Roadmap to becoming an Artificial Intelligence Expert in 2022

Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

Enhanced ChatGPT Clone: Features Agents, DeepSeek, Anthropic, AWS, OpenAI, Assistants API, Azure, Groq, o1, GPT-4o, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active project.

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.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.