CODED-TECHNOLOGIES-SENTIMENT-ANALYSE

A user-friendly python-based GUI which provides sentiment analysis of users' reviews toward a specific TripAdvisor facility

A collection of Python-based NLP projects exploring text processing, sentiment analysis, and language modeling using libraries like NLTK, SpaCy, and Transformers. Includes hands-on implementations with datasets and tutorials for building and evaluating NLP models.

A Python-based Sentiment Analysis web app that detects emotions in text using NLP. Built with TextBlob & Streamlit, it supports single text, bulk, and CSV analysis with real-time visualizations. Designed for scalability with upcoming BERT integration, REST API, and multilingual support.

A Python-based sentiment analysis tool that uses Scikit-Learn and a Naive Bayes classifier to predict tweet sentiment with 95% accuracy.

Description A Python-based web application for analyzing sentiment in movie reviews using NLP techniques and machine learning models. Built with Flask and libraries like NLTK or TextBlob, it provides a user-friendly interface for sentiment classification.

Student Feedback Analyzer is a Python-based desktop application which is developed with a motive to change the existing feedback system used in colleges that uses multiple options in the form of radio button in a form to find out the feedback of the student on a particular subject or a faculty instead use sentiment analysis to find out the feedback score of a subject or faculty from the students feedback. The application uses textblob to find the polarity of a feedback given by the subject and stores it in a database. Later the Administrator can find out the feedback score of each faculty and / or subject using the admin module.