Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

All Algorithms implemented in Python

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

The uncompromising Python code formatter

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

TensorFlow code and pre-trained models for BERT

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

What the f*ck Python? 😱

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

PyTorch Tutorial for Deep Learning Researchers

Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

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 lear…

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.

Open source platform for the machine learning lifecycle

Code samples for my book "Neural Networks and Deep Learning"

Jupyter metapackage for installation, docs and chat

Image augmentation for machine learning experiments.

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Machine Learning Engineering Open Book

An open-source NLP research library, built on PyTorch.

Ongoing research training transformer models at scale

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

Keras implementations of Generative Adversarial Networks.

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

Deep universal probabilistic programming with Python and PyTorch