This project is an NLP (Natural Language Processing) application that classifies BBC news articles into different genres, including sports, politics, entertainment, business, and technology. The classification is done using two different techniques: LSTM and GRU.

AI that automatically classify whether or not a word in a given sentence is complex.

Text Classification

Text mining, Text classification, Applied ML algorithm

This repo demonstrates how to perform topic classification and modeling using Natural Language Processing.

Classification of News articles with ML methods and Transformers

Anti-fraud text classification. Aim to apply NLP technology to combat various forms of fraud, particularly phone scams.

An NLP-based Text (News) Classifier developed using TensorFlow, LSTM, Keras, Scikit-Learn, and Python.

2209678 NLP SYS Final Project created by Natchanon Pollertlam & Vichayuth Saelao

My solution to the practicals of Oxford Deep Learning NLP 2017

Using Natural Language Processing tools from NLTK and various modeling approaches from scikit-learn to classify news articles as "real" or "fake" news.

This project offers advanced techniques in text preprocessing, word embeddings, and text classification. Explore methods like Word2Vec and GloVe, and master Multinomial Naive Bayes for accurate predictions. Dive into the world of text clustering and conquer challenges like unbalanced data.

Some tasks in NLP: Text Classification and Machine Translation

Sentence split, Text classfication, performanc analysis for NLP

TextCNN, Chinese text data mining, 中文文本数据挖掘

News Recommendation System with Python

This repo contains code for toxic comment classification using deep learning models based on recurrent neural networks and transformers like BERT. The goal is to detect and classify toxic comments in online conversations using Jigsaw's Toxic Comment Classification dataset.