WhatsApp Chat Analysis
This WhatsApp chat analysis program takes a chat export file and generates visualizations. It calculates user activity metrics, analyzes temporal and content patterns, and creates visualizations using various libraries. The interactive web application allows users to select specific users and customize visualizations.
Movie Recommendation System
This project aims to develop a movie recommendation system that utilizes a content-based approach to suggest personalized movie suggestions to users. The system will utilize the TMDB 5000 Movie Database from Kaggle to extract relevant movie information and employ machine learning techniques to generate recommendations based on content similarity.
SMS Spam Detection
The project targets the task of classifying electronic messages, such as emails or SMS messages, into two categories: spam and not spam. This classification is crucial for email clients and messaging apps to filter out unwanted or irrelevant messages, improving the overall user experience and reducing exposure to potential phishing scams or malicious content.
Disaster Tweet Prediction
In today's interconnected world, social media platforms like Twitter have become invaluable sources of real-time information. During times of crisis, such as natural disasters, Twitter can be a lifeline for people seeking help and for organizations coordinating relief efforts. However, the sheer volume of tweets can make it difficult to identify those that are truly relevant to a disaster. This is where machine learning comes in. Machine learning algorithms can be trained to classify tweets as either related to a disaster or not. This information can then be used to alert emergency responders and provide them with a clear picture of the situation on the ground.