6075 Open source projects that are alternatives of or similar to Gans

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

A TensorFlow implementation of DeepMind's Differential Neural Computers (DNC)

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Support content for my blog

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

A pedagogical implementation of Autograd

Financial data reader

Ten thousand books, six million ratings

Jupyter notebooks for learning how to use SimpleITK

Recipes for using Python's pandas library

A couple of simple GANs in Keras

中文 Python 笔记

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

Data Analysis Baseline Library

Pangeo website + discussion of general issues related to the project.

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

Proposes neural networks that can generate animation of virtual characters for different actions.

A self driving toy car using end-to-end learning

Practical assignments of the Deep|Bayes summer school 2019

Medical Q&A with Deep Language Models

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

【运筹OR帷幄|数据科学】pandas教程系列电子书

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。

PyTorch and Tensorflow functional model definitions

Code for some of my tutorials

An implementation of WaveNet with fast generation

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)

📔 在学院的书架上发现了一本不带脑子就能看懂的书《Python数据挖掘与实战》

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

Apache Airflow tutorial

Environment for reinforcement-learning algorithmic trading models

Feature Pyramid Networks for Object Detection

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

Some ipython notebooks implementing AI algorithms

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

Build a bot that speaks like you!

Deep Learning Specialization by Andrew Ng on Coursera.

a tensorflow implementation of WGAN

Code repository for O'Reilly book

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

Reference deployment of JupyterHub with docker

数据科学的笔记以及资料搜集

Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.

Normalizing flows in PyTorch. Current intended use is education not production.

What would you say if I told you there is a app on the market that tell you if you have a hotdog or not a hotdog.

My corrections for the Standford class assingments CS231n - Convolutional Neural Networks for Visual Recognition

Utility functions for handling MIDI data in a nice/intuitive way.

Feature exploration for supervised learning

Jupyter notebooks in Russian. Introduction to Python, basic algorithms and data structures

Keras documentation, hosted live at keras.io

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A PyTorch based library for all things neural differential equations

Official SRFlow training code: Super-Resolution using Normalizing Flow in PyTorch

My blogs and code for machine learning. http://cnblogs.com/pinard

A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.

An intro to Python & programming for wanna-be data scientists

Structured data about Panama papers collected from official ICIJ website