amironoff

udpipe

UDPipe: Trainable pipeline for tokenizing, tagging, lemmatizing and parsing Universal Treebanks and other CoNLL-U files

edge

Run .NET and Node.js code in-process on Windows, MacOS, and Linux

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

PugViewEngine

A view engine for ASP.Net MVC using the Pug template engine

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

Non-nativeEnglishGrammarCorrection

corefxlab

This repo is for experimentation and exploring new ideas that may or may not make it into the main corefx repo.

CNTK

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

module-zero-forsaken

ASP.NET Boilerplate - ASP.NET Identity Integration Module

DZ.Tools

Contains methods and data structures to simplify tagged text comparison, automatically builds confusion matrix. Supports html rendering, parsing from html or csv.

PyCon-NLTK-Tutorial

nltk3-cookbook

Code for NLTK3 Cookbook

nltk-trainer

Train NLTK objects with zero code

vc-platform

Virto Commerce B2B Innovation Platform

Stanford.NLP.NET

Stanford NLP for .NET

LMSharp

Language model

CRFSharp

CRFSharp is Conditional Random Fields implemented by .NET(C#), a machine learning algorithm for learning from labeled sequences of examples.

Txt2Vec

Txt2Vec is a toolkit to represent text by vector. It's based on Google's word2vec project, but with some new features, such incremental training, model vector and so on.

RNNSharp

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

deep-learning

Simple example of using the Accord .NET C# library to implement a deep-learning neural network (deep belief network) with machine learning. Solves XOR and an ASCII digit dataset.

what2watch

A list of videos that every software development professional should watch. Curated by Latvian Software Craftsmanship Community.

Mobius

C# and F# language binding and extensions to Apache Spark