Automated NLP sentiment predictions- batteries included, or use your own data

Kaggle Competition: Using deep learning to solve quora's question pairs problem

Kex is a python library for unsupervised keyword extraction from a document, providing an easy interface and benchmarks on 15 public datasets.

Deep Learning and Machine Learning mini-projects. Current Project: Deepmind Attentive Reader (rc-data)

The Centrifuge process, filter and saves the relevant documents as recommendations to the relevant users

Interpretable Models for NLP using PyTorch

Automatic Text Summarization (English/Arabic).

Conditional Sequence Generative Adversarial Network trained with policy gradient, Implementation in Tensorflow

Sentiment Analysis using Stochastic Gradient Descent on 50,000 Movie Reviews Compiled from the IMDB Dataset

Companion code for Introduction to Python for Data Science: Coding the Naive Bayes Algorithm evening workshop

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

A SVM model that classifies the reviews as real or fake. Used both the review text and the additional features contained in the data set to build a model that predicted with over 85% accuracy without using any deep learning techniques.

Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:

Reference implementation of the paper "Word Embeddings for Entity-annotated Texts"

ShortText classification

Topic modelling on financial news with Natural Language Processing

Very deep CNN for text classification

A Python library to conjugate verbs in French, English, Spanish, Italian, Portuguese and Romanian (more soon) using Machine Learning techniques.

Language Identification Toolkit

Scripts utilizing Heartex platform to build brand sentiment analysis from the news