Programming assignments completed in the PG Program for AI ML

Comparison of classifier Algorithms on Diabetes Health Indicators Dataset.

Data Mining project to implement Quinlan's C4.5 decision tree algorithm from scratch for medical data mining using the Thyroid allbp dataset

The goal of this project is to develop a machine learning model that can help banks to identify customers who are likely to churn and take appropriate measures to retain them

Loan Approval Analysis involves building a machine learning model to predict whether a loan will be approved or not based on various customer features

This is our Machine Learning course project. Predict the user based on its cursor movements.

This project analyzes Twitter data to assess public sentiment on U.S. President Joe Biden before and after elections. Using machine learning models (Decision Trees, Random Forests, Naive Bayes, Logistic Regression), it predicts sentiment trends and their potential impact on future elections.

This is a Machine Learning model developed with "Decision Trees Algorithm" and "Random Forest Algorithm" to predict the turnover of HDFC bank with a given dataset of the previous turnovers and features.

Simple Coding exercises involving concepts of Data Science and ML

A fraud detection project developed in KNIME using transaction data, combining statistical methods and machine learning models to identify anomalous patterns and support real-time fraud monitoring through a hybrid analytical architecture.

Customer churn prediction for a bank using supervised learning, handling class imbalance with upsampling and optimizing for F1 score with ROC-AUC reporting.