This project builds a content-based movie recommendation system using the TMDB dataset. By combining metadata features like cast, genres, and directors into a "metadata soup," it calculates movie similarity with vectorizers (Count) and cosine similarity. Ideal for learning content-based filtering and text vectorization techniques.
This project aims to explore the underlying topics within Reddit discussions using advanced natural language processing techniques. By applying topic modeling algorithms like Latent Dirichlet Allocation (LDA), we can identify the dominant themes and patterns in large-scale Reddit datasets.
Recommendations of imdb Movies produced & co-produced by either France or Latin America
Rating: (6/10) The project uses Python libraries and APIs to analyze Reddit data, predict user input, suggest new titles based on cosine similarity, calculate combined scores, and output the best suggestion.
"We used over 2000+ language rows to train our machine learning model, utilizing the scikit-learn library. Our model has achieved an accuracy of 95%."
About Unlock Your Next Favorite Film! Our NLP-powered Movie Recommendation Web App delivers tailored suggestions based on cast, genres, and production companies. Explore a seamless Streamlit interface, also, you can see the description of selected movie. and all movies list.
This project explores sentiment analysis using neural networks
This project is a part of the coursework from CSE718: Petri Net Theory and Modeling of Systems. Our approach was to detect misinformation in social media using Machine Learning Techniques.
Email Spam Detector with 99% accuracy.
Unlock Your Next Favorite Film! Our NLP-powered Movie Recommendation Web App delivers tailored suggestions based on cast, genres, and production companies. Explore a seamless Streamlit interface, also, you can see the description of selected movie. and all movies list.
This is a movie reccomendation system (content based filtering)
An innovative system for filtering and categorizing movie reviews
Movies Recommendation using Machine Learning and Applied Python popular Streamlit library to simplifies the process of web application for data science and machine learning projects
Amazon Product Reviews: Sentiment Analysis with NLP
This repository contains my solution for the Kaggle competition Automated Essay Scoring 2.0. The goal of this project is to develop an automated system capable of scoring essays based on their content and quality using machine learning techniques.
movie recommendation systems aim to predict and suggest movies that align with individual user preferences.
Mini project for content-based music recommendation based on user-specific classification problem.
A Natural Language Processing model to perform Sentiment Analysis of US Airline Customers
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