pvr1 Goto Github PK

pytorch-rbm

Restricted Boltzmann Machines (RBMs) in PyTorch

pytorch-rl

Deep Reinforcement Learning with pytorch & visdom

pytorch-rl-1

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

pytorch-summary

Model summary in PyTorch similar to `model.summary()` in Keras

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorch-tutorial-1

Build your neural network easy and fast

pytorch-wgan

Pytorch implementation of DCGAN, WGAN-CP, WGAN-GP

ranking

Learning to Rank in TensorFlow

reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

restricted-boltzmann-machines-in-pytorch

RBM in Pytorch

rl-adventure

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

rl-quadcopter-2

Teach a Quadcopter How to Fly!

rlkit

Collection of reinforcement learning algorithms

sc-fegan

SC-FEGAN : Face Editing Generative Adversarial Network with User's Sketch and Color

slowfast-networks

implement of slowfast networks

slowfastnetworks

PyTorch implementation of "SlowFast Networks for Video Recognition".

softlearning

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains.

spacy

💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stargan

Official Implementation of StarGAN - CVPR 2018

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

streetlearn

A C++/Python implementation of the StreetLearn environment based on images from Street View, as well as a TensorFlow implementation of goal-driven navigation agents solving the task published in “Learning to Navigate in Cities Without a Map”, NeurIPS 2018

stylegan

StyleGAN - Official TensorFlow Implementation

swagger-petstore

tensor2tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

thai_tts

Thai_TTS is the project about training "Text to Speech in Thai" using Tacotron2 by NVIDIA.

timeseries_fastai

fastai implementation of Timseries classification papers

torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

transformer-xl

transmogrifai

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning