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Assignments from Applied Machine Learning Class (UTD BUAN-6341)

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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.