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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
The fundamental package for scientific computing with Python.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python bindings for FFmpeg - with complex filtering support
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
A Blender script to procedurally generate 3D spaceships
Machine Learning Pipelines for Kubeflow
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…
TensorFlow (Python API) implementation of Neural Style
Pytorch framework for doing deep learning on point clouds.
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch…
Python implementation of the NEAT neuroevolution algorithm
Project page of paper "Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning"
Example of Microservices written using Flask.
Pure-Python gRPC implementation for asyncio
A batch-optimized scaling manager for Kubernetes
Code for the paper Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge (EMNLP 2016). http://arxiv.org/abs/1608.03000
Visual Question Answering in Tensorflow.
A playable implementation of Fully Convolutional Networks with Keras.
Run Google's bazel inside a docker container via a seamless proxy.
Python libraries for Waveshare e-paper series
Node based Gui for creating caffe networks