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

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

Predicts the qualified employee for promotion using Classification

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

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

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

Official Implementation of Track2Vec: Fairness Music Recommendation with a GPU-Free Customizable-Driven Framework EvalRS-CIKM-2022

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

Diabetes prediction using bagging (ensemble methods)

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

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

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

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

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

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.

Predict sale prices via regression models, using PCA, k-means clustering, ensemble models, pipelines, etc.

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

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

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