Here is an extended list of important GitHub repositories related to AI and Machine Learning (ML) across various domains, including natural language processing (NLP), computer vision, reinforcement learning, and more:
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Machine Learning From Scratch
Implementations of ML models from scratch using NumPy only.
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100-Days-Of-ML-Code
A comprehensive guide to learn ML in 100 days.
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fastai/fastai
High-level library built on PyTorch, focused on making DL accessible.
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ml-course
Open materials for studying machine learning algorithms.
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Hands-On ML with Scikit-Learn, Keras, and TensorFlow
Notebooks for the book "Hands-On Machine Learning."
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Deep Learning Specialization on Coursera
Jupyter notebooks from Andrew Ng's Coursera course.
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PyTorch Examples
A set of example scripts for PyTorch.
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TensorFlow Models
TensorFlow implementations of ML and DL models.
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Dive into Deep Learning
Interactive deep learning book with code, math, and discussions.
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Deep Learning for Computer Vision
DL implementations focused on computer vision.
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Transformers
Hugging Face's popular library for transformers in NLP.
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spaCy
Industrial-strength NLP library in Python.
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stanfordnlp
Official Python wrapper for Stanford NLP tools.
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NLTK
Natural Language Toolkit — classic library for NLP.
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OpenNLP
Apache library for processing natural language text.
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OpenCV
Library for computer vision, image processing, and machine learning.
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Detectron2
Facebook's research library for object detection and segmentation.
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DeepLab
Semantic image segmentation using DeepLab models.
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StyleGAN2
Official repository for StyleGAN2, used for generating images.
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YOLOv5
Real-time object detection with YOLOv5.
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OpenAI Gym
Toolkit for developing RL environments and algorithms.
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Stable-Baselines3
A set of RL algorithms based on PyTorch.
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RLlib
A scalable library for reinforcement learning.
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DeepMind Lab
A 3D environment for RL research.
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dopamine
Google's lightweight RL framework.
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AI Fairness 360
IBM's toolkit to detect and mitigate bias in ML models.
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Themis-ML
A library for fairness-aware ML.
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What-If Tool
Visual interface for ML fairness and interpretability.
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Awesome Machine Learning
A curated list of awesome ML frameworks, libraries, and software.
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Awesome AI
A curated list of AI-related tools, datasets, and resources.
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Data Science Notebooks
Jupyter notebooks for data analysis, visualization, and ML.
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Model Zoo for PyTorch
Pre-trained PyTorch models for various tasks.
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AI Papers with Code
A collection of AI papers accompanied by their implementations.
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These repositories cover a wide range of applications and techniques in AI and ML, making them valuable resources for learning and project development. Let me know if you want recommendations specific to a particular area!