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An opinionated list of awesome Python frameworks, libraries, software and resources.
All Algorithms implemented in Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A curated list of awesome Machine Learning frameworks, libraries and software.
🎨 Diagram as Code for prototyping cloud system architectures
Streamlit — A faster way to build and share data apps.
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Official Code for DragGAN (SIGGRAPH 2023)
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,…
We have made you a wrapper you can't refuse
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.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Turns Data and AI algorithms into production-ready web applications in no time.
📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Avatars for Zoom, Skype and other video-conferencing apps.
SQL databases in Python, designed for simplicity, compatibility, and robustness.
Machine Learning Engineering Open Book
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)
StyleGAN2 - Official TensorFlow Implementation
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Advanced Python Mastery (course by @dabeaz)
Minimal and clean examples of machine learning algorithms implementations
A collection of libraries to optimise AI model performances
Build resilient language agents as graphs.