An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

A collection of research papers on decision, classification and regression trees with implementations.

Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017

A curated list of data mining papers about fraud detection.

Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints

A curated list of gradient boosting research papers with implementations.

A java classifier based on the naive Bayes approach complete with Maven support and a runnable example.

ncnn example: mask detection: anticonv face detection: retinaface&&mtcnn&&centerface, track: iou tracking, landmark: zqcnn, recognize: mobilefacenet classifier: mobilenet object detecter: mobilenetssd

Natural language detection library for Rust. Try demo online: https://whatlang.org/

ERRor ANnotation Toolkit: Automatically extract and classify grammatical errors in parallel original and corrected sentences.

The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch

Facial Emotion Recognition on FER2013 Dataset Using a Convolutional Neural Network

A Machine Learning classifier for recognizing the digits for humans 🎰

A sophisticated smart symptom search engine

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

yet another general purpose naive bayesian classifier.

A License Classifier

A pytorch implemented classifier for Multiple-Label classification

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can…