Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
There are 64,334 repositories under machine-learning topic.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Deep Learning for humans
List of Computer Science courses with video lectures.
scikit-learn: machine learning in Python
Tesseract Open Source OCR Engine (main repository)
The world's simplest facial recognition api for Python and the command line
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
Deepfakes Software For All
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
The Julia Programming Language
100 Days of ML Coding
DeepFaceLab is the leading software for creating deepfakes.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Caffe: a fast open framework for deep learning.
Learn how to responsibly develop, deploy and maintain production machine learning applications.
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
💫 Industrial-strength Natural Language Processing (NLP) in Python
AI-Powered Photos App for the Decentralized Web 🌈💎✨
⛔️ 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
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
The fastai deep learning library
Streamlit — The fastest way to build data apps in Python
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.