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High-performance TensorFlow library for quantitative finance.
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.
A face recognition for simpsons character build with flax
Flax is a neural network library for JAX that is designed for flexibility.
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
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
A topic-centric list of HQ open datasets.
Torch implementation of neural style algorithm
Handout for the tutorial "Creating publication-quality figures with matplotlib"
Painlessly create beautiful matplotlib plots.