High-performance TensorFlow library for quantitative finance.

Set up a personal VPN in the cloud

Scenic: A Jax Library for Computer Vision Research and Beyond

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

This project was moved to: https://github.com/coax-dev/coax

Google Research

MiniFold: Deep Learning for Protein Structure Prediction inspired by DeepMind AlphaFold algorithm

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

JAX-based neural network library

A face recognition for simpsons character build with flax

Flax is a neural network library for JAX that is designed for flexibility.

Implementations of phase recovery algorithms.

Recurrent Geometric Networks for end-to-end differentiable learning of protein structure

Standardized data set for machine learning of protein structure

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

Example implementation of the DeepStack algorithm for no-limit Leduc poker

Scala client for the Twitter streaming api

Efficient, reusable RNNs and LSTMs for torch

Minimalist Jekyll Template, dark and light themes

Utilities and monitors for machine learning experiments, web client included.

Reinforcement learning with unsupervised auxiliary tasks

Speed up PixelCNN++ image generation by up to a 183 times

A living collection of deep learning problems

Automatically exported from code.google.com/p/word2vec

Keras WaveNet implementation

Auto RSVP yes for meetup group events.

A topic-centric list of HQ open datasets.

Torch implementation of neural style algorithm

Handout for the tutorial "Creating publication-quality figures with matplotlib"