Classification and clustering in dataset of news articles.

2021 홍익대학교 산업공학과 졸업 프로젝트

A machine learning system that takes a comment and classifies it as offensive or non-offensive (neutral). This system will be trained in a data set with comments in which the tags (insult or non-insult) are known. Classification algorithms used: Naive Bayes, SVM, Random Forest.

Simple provisioning with rake tasks

Python for Data science #sentiment analyse using tensorflow#CNN#NLP#BOW

benchmark different techniques of text classification in order to predict of Amazon review polarity

Pair a smartphone to a bow

Using NLP and a smart chatbot, this project gauges customer sentiments online, offering customization and real-time feedback. Employing TF-BOW-LDA and ML models, it empowers e-commerce decisions, culminating in an NLP course at uOttawa in 2023.

Bow bundle of Klipper

Practical works for natural language processing course at university.

Text Classification that works on identifying different authors writing styles in Gutenberg Digital Books | NLP.

Sentiment analysis on reviews of the movie from the imdb movie review Dataset

This project is a SMS spam classifier which detect whether the SMS is spam or ham using the multinomial Naive Bayes algorithm along the side of BOW/TF-IDF in NLP

A macro to get free metal shards in Horizon Forbidden West using Logitech G Hub

Image Classificaition

The Bow Framework WebSite

Sample Mobile Validation using Bow (updated to 0.6.0 with SwiftUI)

Build a simple search engine based on TF-IDF using python