Data Science & Machine Learning with GenAI

The Car Price Predictor project is a web-based application that allows users to estimate the selling price of used cars by inputting key details, such as mileage and year of manufacture. The application leverages a linear regression model, trained on historical data, to generate price predictions. Users can interact with…

The Loan Prediction project is a web-based application that leverages data science to estimate loan approval outcomes. Users enter vital financial details, such as income and credit score, into an intuitive interface built with Flask. The system employs a Random Forest model, developed using Scikit-learn, which is trained on historical…

The Wine Quality Predictor project is a machine learning-based application designed to assess wine quality based on key chemical properties. Using a linear regression model built with Scikit-learn, the system analyzes features like acidity, alcohol content, and pH level to estimate a quality score. The project evaluates the model's accuracy…

The IPL Score Predictor project is a machine learning-based model designed to estimate the final score of an IPL match based on key in-game factors. Using a linear regression model built with Scikit-learn, the system analyzes inputs like current runs, wickets, and overs to predict the total score at the…

The Movie Magic project is a machine learning-powered recommendation system designed to suggest movies based on user preferences and past ratings. Using collaborative filtering and content-based recommendation techniques, the model analyzes user behavior, movie details, and rating patterns to uncover personalized movie suggestions. The system evaluates its recommendation accuracy by…

The E-Commerce Customer Spending Predictor is a machine learning-based project that helps businesses understand and forecast customer spending behavior. Using a linear regression model built with Scikit-learn, the system analyzes key factors such as session length, time spent on the app, and other user interactions to estimate yearly spending. This…

The Diabetes Prediction project is a machine learning-based model designed to assess the likelihood of diabetes in individuals based on key health indicators. The dataset, sourced from Kaggle, originates from the National Institute of Diabetes and Digestive and Kidney Diseases and includes features such as Number of Pregnancies, Insulin Level,…

The Arrhythmia Classification project leverages machine learning to detect and classify different types of arrhythmia using ECG data. The dataset consists of 452 samples and 16 classes, including both normal and various arrhythmia conditions. A major challenge is the high-dimensional nature of the data, with 279 features exceeding the number…