Projects completed as a part of IIIT-Delhi's Post Graduation Diploma in Computer Science and Artificial Intelligence.

Predicts the qualified employee for promotion using Classification

My solutions to the data analysis and forecasting case study held by Bella & Bona

Course project for Stanford's STATS 315B (Modern Applied Statistics: Learning II).

The goal of this report was to identify which variable best predicts divorce using decision trees and other ensemble methods. In the data set, Class is the response variable, with 0 = still married and 1 = divorced.

Intuitive Package for Heterogeneous Ensemble Meta-Learning (Classification, Regression) that is fully-automated

My Final Project for my Introduction to Data Science course at Simmons University.

Evaluate the creditworthiness of individuals.Develop a credit scoring model that evaluates the creditworthiness of individuals based on historical data.Help financial institutions assess risk more accurately.

Test and comparison of ensemble method with naive bayes classifier on 5 different data sets.

A collection of AI and ML projects demonstrating various techniques, algorithms, and applications.

Using deep learning to predict whether students can correctly answer diagnostic questions

Instructional materials (course files) for the BBT4206 course (Business Intelligence II) using R. Topic: Ensemble Methods.

Comparison of ensemble learning methods on diabetes disease classification with various datasets

Build a classification model to predict clients who are likely to default on their loans. Give recommendations to the bank on important features to consider while approving a loan. Concepts Used: Logistic Regression, Decision Trees, Random Forests, and Ensemble Methods

User documentation website for the Sulis tier 2 HPC service. Built using Jekyll.

This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.

This project presents a ML based solution using Ensemble methods to predict which visa applications will be approved and thus recommend a suitable profile for applicants whose visa have a high chance of approval

This is an assignment from my Machine Learning for Mechanical Engineers course that demonstrates an understanding in decision trees and ensemble methods using scikit-learn.

Identification of Lung Cancer in Smoker Person Using Ensemble Methods Based on Gene Expression Data. Presented in IC2IE and published to IEEE.

Capstone project #2 for the Harvard University Professional Certificate in Data Science