1128 Open source projects that are alternatives of or similar to Advanced Deep Learning With Keras

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

State Representation Learning (SRL) zoo with PyTorch - Part of S-RL Toolbox

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Collection of generative models in Tensorflow

A curated list of dedicated resources and applications

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

A Pytorch implementation for the ZeroSpeech 2019 challenge.

Comparison of Generative Models in Tensorflow

Focal Frequency Loss for Generative Models

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

Machine learning, in numpy

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

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Tensorflow implementation of conditional variational auto-encoder for MNIST

Paper collection of Neural Text Generation

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

🙄 Difficult algorithm, Simple code.

Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

[CVPR2020] Adversarial Latent Autoencoders

Tensorflow implementation of adversarial auto-encoder for MNIST

Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).

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.

Tensorflow implementation of variational auto-encoder for MNIST

Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

TensorFlow and Deep Learning Tutorials

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

Stochastic Adversarial Video Prediction

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

Generative Adversarial Networks and Autoencoders for 3D Shapes

Deep Learning sample programs using PyTorch in C++

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

Unofficial PyTorch Implementation of SUM-GAN from "Unsupervised Video Summarization with Adversarial LSTM Networks" (CVPR 2017)

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

Aim — a super-easy way to record, search and compare 1000s of ML training runs

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Deep Reinforcement Learning with pytorch & visdom

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Awesome paper list with code about generative adversarial nets

Next RecSys Library

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

​TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.

An AI for Music Generation

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

StarCraft II - pysc2 Deep Reinforcement Learning Examples

基于金融-司法领域(兼有闲聊性质)的聊天机器人，其中的主要模块有信息抽取、NLU、NLG、知识图谱等，并且利用Django整合了前端展示,目前已经封装了nlp和kg的restful接口

Solutions of Reinforcement Learning, An Introduction

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework