Machine Learning · GitHub

This repo provides :zap: fast:zap: semantic segmentation models on CityScapes/Camvid DataSet by Pytorch

A Wiki containing helpful information for new and existing students of the Machine Learning Nanodegree at Udacity. Written by students of the Nanodegree.

Neural Network with Style Synthesis

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

implementation of "DCCRN-Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement" by pytorch

A list of awesome Machine Translation frameworks, libraries, software and papers

一个为ElectronBot机器人和瀚文键盘（HelloWorldKeyboard）开发的上位机软件（包含机器人USB操作SDK和瀚文键盘HID操作SDK），采用Windows App SDK框架编写界面。 A host computer software developed for ElectronBot robots (including robot USB operation SDK), using the Windows App SDK framework to write UI.

A more than 1000X faster paralleled LSTM-CRF implementation modified from the slower version in the Pytorch official tutorial (URL:https://pytorch.org/tutorials/beginner/nlp/advanced_tutorial.html).

Clean baseline implementation of PPO using an episodic TransformerXL memory

Euclidean Neural Networks

A tutorial on TensorFlow

MINE: Mutual Information Neural Estimation in pytorch (unofficial)

TensorFlow2.0 官方教程翻译，基本概念讲解、实战项目、TensorFlow2.0编程技巧。

This repository collates a number of MATLAB examples demonstrating Scientific Machine Learning (SciML) and Physics Informed Machine Learning.

Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.

pytorch implementation of the different DeepGaze models

Official code for Cotatron @ INTERSPEECH 2020

Learning and Building Convolutional Neural Networks using PyTorch

A tool for efficient semi-supervised video object segmentation (great results with minimal manual labor) and a dataset for benchmarking

a repo sharing Bayesian Neural Network recent papers

Auto-Annotate - Automatically annotate your entire image directory by a single command. As simple as saying - "Annotate all the street sign (label) in the autonomous car dataset (directory)" and BAM! DONE. Each and every image with a street sign in the diverse dataset directory containing images of all sorts which have a street sign are filtered and the segmentation annotation is performed in a single command. The Auto-Annotate tool provides auto annotation of segmentation masks for the objects in the images inside some directory based on the labels. Auto-Annotate is able to provide automated annotations for the labels defined in the COCO Dataset and also supports Custom Labels.

Feature Books for Machine Learning

Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are said to outstand given the data is pre-processed well. On the same theory here is my approach for Detecting whether a plant leaf is healthy or unhealthy by utilizing the classical Machine Learning Models, Pre-processing the Image Data. The data was fed to 7 Machine Learning Models with 10 fold cross-validation out of which Random Forest Classifier outperformed all the other models giving an accuracy of 97% on the test set.