Data Science Intern
Projects completed:1. Titanic Survival Prediction : Used the Titanic dataset to build a model that predicts whether apassenger on the Titanic survived or not. This is a classic beginner project with readily available data.The dataset used for this project contains information about individual passengers, such as their age, gender, ticket class, fare, cabin, and whether or not they survived.2.Movie Rating Prediction using Python : Built a model that predicts the rating of a movie based on features like genre, director, and actors.The goal is to analyze historical movie data and develop a model that accurately estimates the rating given to a movie by users or critics. This project provides insights into the factors that influence movie ratings and allows to build a model that can estimate the ratings of movies accurately.3. Credit Card Fraud Detection : Built a machine learning model to identify fraudulent credit card transactions. Preprocessed and normalized the transaction data, handled class imbalance issues,and splitted the dataset into training and testing sets. Trained a classification algorithm, such as logistic regression or random forests, to classify transactions as fraudulent or genuine.Evaluated the model's performance using metrics like precision, recall, and F1- score, and consider techniques like oversampling or undersampling for improving results.