An Open Source Machine Learning Framework for Everyone
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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Tensors and Dynamic neural networks in Python with strong GPU acceleration
《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。
Learn AI Engineering! Learn it. Build it. Ship it for others.
Deep Learning for humans
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Clone a voice in 5 seconds to generate arbitrary speech in real-time
100 Days of ML Coding
We write your reusable computer vision tools. 💜
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Learn how to develop, deploy and iterate on production-grade ML applications.
Streamlit — A faster way to build and share data apps.
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
500 AI Machine learning Deep learning Computer vision NLP Projects with code
💫 Industrial-strength Natural Language Processing (NLP) in Python
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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.