𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 (𝗠𝗖𝗣) 𝗕𝗮𝘀𝗲𝗱 𝗖𝗟𝗜 𝗔𝗜 | 𝗧𝗼𝗼𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 | 𝗚𝗲𝗺𝗶𝗻𝗶 𝟮.𝟬

A free, private, open-source, and minimalist web app for discovering movies and TV shows

Designed and deployed an AI-powered sentiment analysis dashboard using Natural Language Processing and Machine Learning, enabling real-time review classification, model interpretability, and business insight generation.

🎬 Binary Sentiment Analysis on the IMDB 50K dataset. A classic NLP pipeline utilizing NLTK for preprocessing, TF-IDF for vectorization, and Logistic Regression for high-accuracy text classification.

Professional VADER sentiment analysis on IMDb movie reviews with comprehensive evaluation and error analysis (📉,📈)

Movie Review Management System: Java app to add, search, list, sort, and manage movie reviews. Includes file I/O for saving and uploading reviews.

Movie Review Sentiment Analysis using NLP and Machine Learning

Sentiment classification of movie reviews using NLTK and Logistic Regression

Analyzing movie reviews sentiment analysis using LSTM Model

This project performs sentiment analysis on movie reviews from the IMDB dataset using deep learning techniques. The goal is to classify user feedback as positive or negative based on the textual content of reviews. Two models are implemented: LSTM and BiLSTM, to compare their performance in understanding sequential data.

Advanced sentiment analysis system for movie reviews using machine learning. Compares Logistic Regression, Naive Bayes, and SVM models with interactive prediction interface and comprehensive text preprocessing pipeline.

A project finished 04-21-2026 as part of the TripleTen Data Science program using real-world data and mimicking real-world project requirements. Task was to train a machine learning model to classify IMDB film reviews as positive or negative. The best F1 score achieved was 0.88.

Customer Feedback Analytics using NLP and Machine Learning on 50,000 IMDb Movie Reviews with TF-IDF, Bag of Words, and Logistic Regression.

Python-based scraper for collecting movie data from The Numbers and user reviews from IMDb, useful for text mining, sentiment analysis, and forecasting

Movie Review Sentiment Analysis using NLP and Machine Learning

A program that classifies text as positive or negative based on IMDb movie review database.

Sentiment analysis of IMDb movie reviews using TF-IDF and Logistic Regression

Sentiment analysis on IMDb movie reviews using LSTM-based Recurrent Neural Networks (unidirectional, bidirectional, stacked) in Keras/TensorFlow. Includes visualisations, model architecture, and suggestions for future improvements.

Machine learning Model understanding Human sentiments through reviews.

IMDb sentiment classification using neural networks, GloVe embeddings, LSTM, and Flask deployment.