5921 Open source projects that are alternatives of or similar to Neural Painters

Kaggle Struggle

CARTO Python package for data scientists

A machine learning project. Turn on your webcam. Mona Lisa's eyes will follow you around.

Paper: CVPR2018, Learning Rich Features for Image Manipulation Detection

Quantitative finance research tools in Python

Some code examples gathered during my Month of Julia.

for code created as part of http://studywolf.wordpress.com

Simplified implementations of deep learning related works

18.335 - Introduction to Numerical Methods course

Python code for bayesian optimization using Gaussian processes

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

👩🏻‍⚕️Covid-19 estimation and forecast using statistical model; 新型冠状病毒肺炎统计模型预测 (Jan 2020)

What scientific programmers must know about CPUs and RAM to write fast code.

Tutorial for using Kitti dataset easily

A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

TensorFlow JS models for MIRNet for low-light image enhancement.

Simple plotting library that wraps Matplotlib and integrated with DataFrames

A collection of various deep learning architectures, models, and tips

This is the code for "Neural DIfferential Equations" By Siraj Raval on Youtube

A fast and lightweight AutoML library.

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

A clear, concise, simple yet powerful and efficient API for deep learning.

A library of metrics for evaluating recommender systems

This is an LSTM stock prediction using Tensorflow with Keras on top.

Decaf is DEPRECATED! Please visit http://caffe.berkeleyvision.org/ for Caffe, the new framework that has all the good things: GPU computation, full train/test scripts, native C++, and an active community!

An automatic beatmap generator using Tensorflow / Deep Learning.

A collection of all my datasets

Pytorch implementation of HighRes-net, a neural network for multi-frame super-resolution, trained and tested on the European Space Agency’s Kelvin competition.

The accompanying files for the book 'Dataviz with Python and JavaScript'

The BlazeFace face detector model implemented in PyTorch

Notes, Codes, and Tutorials for the Deep Learning Course <which I taught at ChinaHadoop>

🌱 Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis

Compared performance of KNN, SVM, BPNN, CNN, Transfer Learning (retrain on Inception v3) on image classification problem. CNN is implemented with TensorFlow

中国象棋alpha zero程序

An implementation of the ideas from this paper https://arxiv.org/pdf/1803.10122.pdf

《Machine Learning: A Probabilistic Perspective》（Kevin P. Murphy）中文翻译和书中算法的Python实现。

Simple Implementation of many GAN models with PyTorch.

《统计学习方法》的代码实现

[电影推荐系统] Based on the movie scoring data set, the movie recommendation system is built with FM and LR as the core(基于爬取的电影评分数据集，构建以FM和LR为核心的电影推荐系统).

A neural network that transforms a design mock-up into a static website.

A collection of tutorials on neural networks, using Theano

Home for Elasticsearch examples available to everyone. It's a great way to get started.

Github repo to upload demo files of youtube videos and linkedin

This is the code for the "Classifying Data using Gradient Descent" by Siraj Raval on Youtube

18.S096 three-week course at MIT

Implemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.

Sample implementation of Neural Ordinary Differential Equations

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

Machine Learning in Finance: From Theory to Practice Book

Running parametric t-SNE by Laurens Van Der Maaten with Octave and oct2py.

Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller

An implementation of some of the tools used by the winner of the box plots competition using scikit-learn.

This is the PyTorch implementation of VGG network trained on CIFAR10 dataset

个人的技能树仓库，主要包含个人机器学习以及深度学习的笔记

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection