Machine Learning Assignments

This repo includes implementation of various machine learning models to predict target variable (continuous/label). The series of assignments are a part of Graduate class of Applied Machine Learning (UTD BUAN 6341).

• Assignment 1 – Linear and Logistic Regression with Gradient Descent Algorithm
• Assignment 2 – Support Vector Classification with Linear, Radial and Polynomial Kernel, Decision Tree Classifier, Pruned Decision Tree Classifier, and AdaBoost Decision Tree Classifier
• Assignment 3 – k-Nearest Neighbors Classifier, Artificial Neural Network Classifier
• Assignment 4 – ANN Classifier run on features created using 1) clustering algorithms – a) k-Means Clustering and b) Expectation Maximization, 2) feature selection technique using Random Forest Feature Importance and feature transformation techniques - a) Principal Component Analysis, b) Independent Component Analysis, and c) Random Projections, and 3) k-Means Clustering features with features selected using Random Forest Feature Importance and Principal Components

About Data

• Seoul Bike Sharing Demand Dataset – The dataset contains information regarding number of bikes rented on an hourly basis for a year and includes prevailing weather conditions.
• Framingham Heart Study Dataset – The chronic heart diseases dataset contains information regarding the chance of contracting a chronic heart disease after 10 years based on demographic, behavioral, current and past medical history.