7479 Open source projects that are alternatives of or similar to Deep Learning With Python

由淺入深的深度學習資源 Collection of deep learning materials for everyone

Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs

머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

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

Official repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)

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

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

Official PyTorch implementation of "Artist Style Transfer Via Quadratic Potential"

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

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

Stochastic Adversarial Video Prediction

DCGAN image generator 🖼️.

pytorch 包教不包会

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

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.

Synthetic Data Generation for tabular, relational and time series data.

The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Spectral Normalization for Keras Dense and Convolution Layers

Projecting images to latent space with StyleGAN2.

Implementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training

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

Collection of generative models in Tensorflow

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Using Machine Learning to predict the type of exercise from movement data

Periodic Spatial Generative Adversarial Networks

Code for "A-NICE-MC: Adversarial Training for MCMC"

The Simplest DCGAN Implementation

music generation with a classifying variational autoencoder (VAE) and LSTM

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

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

Keras tutorial for beginners (using TF backend)

Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.

Solve captcha without manually labeling a training set

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

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

Machine learning, in numpy

Interactive Image Generation via Generative Adversarial Networks

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).

Some interesting TensorFlow tutorials for beginners.

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

Code for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

PyTorch implementation of "Auto-Encoding Variational Bayes"

🎨 Artistic neural style transfer with tweaks (pytorch).

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.

Neural Paiters

Protein function prediction using a variational autoencoder

This toolbox is support material for the book on CNN (http://www.convolution.network).

A Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.

Image-to-image translation with conditional adversarial nets

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

GAN in Tensorflow to be run via Linux command line

Awesome Generative Adversarial Networks with tensorflow