24-2 콘텐츠프로그래밍기초 기말 프로젝트 개인 과제

♦️ Twitter US Airline Sentiment Analysis ♦️ Applied text preprocessing, NLP, and sentiment classification to analyze positive, neutral, and negative tweets. Created visualizations like sentiment distribution, airline comparisons, and word clouds for key insights. Delivered a cleaned dataset, insightful analysis, and automated PowerPoint report.

A web application that allows users to upload and analyze PDF documents. The tool provides instant text analysis including word count, character count, sentence statistics, and word frequency visualization. Users can easily upload files through drag-and-drop or file selection, and toggle between including or excluding common words in analysis.

A full-stack text analysis application with Keycloak authentication, implementing word tokenization, sentence boundary detection, and longest word extraction algorithms with Redis caching for performance optimization.

A tool to search for n-grams within ancient Latin texts and display their frequency

Data science projects focused on exploring and analyzing Game of Thrones dialogues and characters using natural language processing (NLP) techniques, including sentiment analysis, word frequency, and named entity recognition.

Automate merging of DOC, DOCX, and PDF files with word frequency analysis. Streamlines document consolidation for large-scale projects.