Word2Vec Library

Identify question pair with the same intent using Convolutional Neural Network

This project incorporates Hierarchical document clustering of the Kaggle forum posts using data from Meta Kaggle. Includes fine-tuned vectors using GoogleNews embeddings.

Skip-Gram Model From Scratch

Teaching a computer to recognize toxic comments using Google Cloud Natural Language Processing tools. Submitted for entry into the MLH event at UT-Dallas HackDFW 2019.

Different ML techniques examples

Ce fut mon prémier projet NLP où j'ai réalisé la détection de spam en utilisant les algorithmes d'embedding pour encorder mes textes. J'ai utilisé Random Forest et Milti-Layres Perceptrons pour la phase de classification. Ce qui a pemit l'obtension des précisions respective de 97% et 98%. J'ai aussi appris à documenter mes codes via sphinx

MigrationInTheTimes: Visualising changes in the construction of meaning with Word Vector Space

Coursera's Natural Language Processing specialization

Word embedding and Sentiment analysis using 2 layer Neural Network

An implementation of definition evaluation project as a class project within the Artificial Intelligence class.

Data / description here: https://www.kaggle.com/c/inls690-270-funny-news-headline

News Classifier App that appropriately classifies a news article as real news or fake news using Deep Learning LSTM and model is deployed using flask

Word2Vec Library

中文多类别文本分类

This is final project of Information Retrieval course which is implementation of a search engine

Word2Vec Library

This repository contains code for learning word2vec embeddings using skip-gram model

Intelligent search for the most relevant questions on stackoverflow.com for a machine learning query.