Rating: (8/10): ThematicBot is an AI-based chatbot developed using TensorFlow, spaCy, and KMeans clustering to generate contextually appropriate responses, improving user experience through tokenization, embedding, and Tkinter library management.

Telegram bot for translation messages to certain languages

Multifunctional system for automatic text and language analysis

The objective of this assignment is to extract textual data articles from the URL and perform text analysis to compute variables.

The Sentiment Analysis App, built with tkinter and TextBlob, features a main window with a violet background. Users input text in a provided box, clicking "Analyze Sentiment" triggers analysis. The app checks for empty input, displays results (Positive, Neutral, Negative) in a label below. Continuous event handling keeps the app responsive.

The global supply chain is a crucial driver of the world economy, enabling the movement of goods and services worldwide and directly impacting economic growth. Analyzing sentiment surrounding the global supply chain in March 2024 reveals whether it's positive or negative, offering insights into improvements and disruptions.

This a repo of Python project on NLP

This is a sentiment analysis project based on pretrained modules like TextBlob and VADER on Amazon_Food_Reviews dataset.

Script designed to perform sentiment analysis on news articles retrieved from the NewsAPI based on a user-defined keyword.

Sentiment Analysis of Amazon Food Reviews to the customer ratings using VADER, TextBlob and Flair

A simple Python Program to Analyze Sentiments using TextBlob Python Library.

This represents the final capstone project in my HyperionDev Data Science (fundamentals) course. A dataset of Amazon customer reviews is analysed using natural language processing.

I made a program that allows us to correct or predict the word we misspelled.

Uses streaming twitter data based on custom keyword to generate the sentiment of users around that keyword using TextBlob.

2022년 1학기 팀 프로젝트 : COVID-19 기간 트위터 텍스트 데이터 분석

I performed sentiment analysis aimed at determining the sentiment of 50000 imDB movie reviews, whether they are positive, negative, or neutral. I employed various NLP approaches including lexicon based approaches, machine learning models, PLM models, and hybrid models, and assessed the performance on each type of model.

tweety scrape all the tweets using python and selenium with No API rate limits. No restrictions. Extremely fast.

2023년 7월 논문게재(한국벤처창업연구) : COVID-19에 따른 글로벌 창업 트렌드 분석: Cruchbase를 중심으로(Analysis of Global Entrepreneurship Trends Due to COVID-19: Focusing on Crunchbase, 1저자