Popular GitHub Repositories for Bag Of Words

A modern IDE for writing classical Chinese poetry 格律诗编辑程序

This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.

Simple NLP in Rust with Python bindings

NLP Functions for amplifying negations, managing elisions, creating ngrams, stems, phonetic codes to tokens and more.

Hybrid Code Networks https://arxiv.org/abs/1702.03274

D-Lab's 9 hour introduction to text analysis with Python. Learn how to perform bag-of-words, sentiment analysis, topic modeling, word embeddings, and more, using scikit-learn, NLTK, gensim, and spaCy in Python.

BERT ??? ??? ??? ??? ?? ??? (BERT Contextualized Topic Models)

A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link

Website application for fashion recommendation using machine learning.

Natural Language Processing with Python, Python ile Dogal Dil Isleme

Using Natural Language Processing, Data Visualizations and Classification Algorithms of Machine Learning

Project on how to predict sentiment on movies review lectured by Andrew Trask.

意味表現学習

The goal of this project is to design a classifier to use for sentiment analysis of product reviews. Our training set consists of reviews written by Amazon customers for various food products. The reviews, originally given on a 5 point scale, have been adjusted to a +1 or -1 scale, representing a positive or negative review, respectively.

IMDB Movie Reviews - Text preprocessing and classification. Includes BOW model, TF_IDF, VADER entiment analysis, Topic Modelling using Latent Dirichlet Allocation and Word Embeddings. (Python)

Natural Language Processing In Actions

Sentiment analysis of the restaurant reviews from YELP dataset using BoW, TF-IDF, Word2Vec, Doc2Vec, Glove and BERT.

Natural language processing tools for Haskell with emphasis on performance

In this project, task involves analyzing the content of the articles to extract key concepts and themes that are discussed across the articles to identify major themes/topics across a collection of BBC news articles.