998 Open source projects that are alternatives of or similar to Torch Ac

Recurrent Neural Network using randomized SMILES strings to generate molecules

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

Handwritten Text Recognition (HTR) system implemented with TensorFlow.

AAAI 2018 - Unsupervised video summarization with deep reinforcement learning (PyTorch)

Deep Q-Learning Network in pytorch (not actively maintained)

[파이썬과 케라스로 배우는 강화학습] 예제

A selection of state-of-the-art research materials on decision making and motion planning.

Collection of Deep Reinforcement Learning algorithms

Deep-Plant: Plant Classification with CNN/RNN. It consists of CAFFE/Tensorflow implementation of our PR-17, TIP-18 (HGO-CNN & PlantStructNet) and MalayaKew dataset.

Application of machine learning to the Coinbase (GDAX) orderbook

Stock Trading Bot using Deep Q-Learning

A minimalist environment for decision-making in autonomous driving

Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"

SharpNEAT - Evolution of Neural Networks. A C# .NET Framework.

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

This is a Python 3.0 project for analyzing stock prices and methods of stock trading. It uses native Python tools and Google TensorFlow machine learning.

TensorFlow implementation of "Tracking the World State with Recurrent Entity Networks".

Image Captioning: Implementing the Neural Image Caption Generator with python

Computer code collated for use with Artificial Intelligence Engines book by JV Stone

My Reading Lists of Deep Learning and Natural Language Processing

Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

Solutions of Reinforcement Learning, An Introduction

Seamless, distributed, real-time integration of Blender into PyTorch data pipelines

An evolving guide to learning Deep Learning effectively.

📡 Organized Resources for Deep Learning Researchers and Developers

tensorflow deep RL for driving a rover around

Deep Reinforcement Learning library for humans

A collection of machine learning examples and tutorials.

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

Recent Deep Learning papers in NLU and RL

Some notebooks

Accompanying code for Paperspace tutorial "Build an AI to play Dino Run"

OpenAI Gym environments for an open-source quadruped robot (SpotMicro)

The Tensorflow code and a DeepMind Lab wrapper for my article "Meta-Reinforcement Learning" on FloydHub.

Open-source simulator for autonomous driving research.

Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft

Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.

Computational framework for reinforcement learning in traffic control

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Conversational AI Reading Materials

Implement AlphaZero/AlphaGo Zero methods on Chinese chess.

Applying Reinforcement Learning in Quantitative Trading

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Platform for backtesting and live-trading intraday Stock/ETF/ELW using recurrent neural networks

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

A power network simulator with a Reinforcement Learning-focused usage.

Rainbow: Combining Improvements in Deep Reinforcement Learning

Who Let The Dogs Out? Modeling Dog Behavior From Visual Data https://arxiv.org/pdf/1803.10827.pdf

RNN-based generative models for speech.

The Official Deep Learning Framework for Route-based Place Recognition

parsing scene images with understanding geometric perspective in the loop

Reversi reinforcement learning by AlphaGo Zero methods.

Visualization Toolbox for Long Short Term Memory networks (LSTMs)