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Applied Machine Learning

In this class, we had 3 assignments each tackling a different Machine Learning model and dataset. Files with the .ipynb extension are code; files with the .pdf extension are reports.

Summary

  • Project 1: implementing K-Nearest Neighbour (KNN) and Decision Tree (DT) models for classifying health-related data (Hepatitis patient survival, signs of diabetic retinopathy)
  • Project 2: implementing Logistic Regression and Multi-class Regression models for classifying text-related data (positive/negative movie reviews, newsgroup categories)
  • Project 3: implementing a Multi-layer perceptron (MLP) for classifying image-based data (types of clothing articles)

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Implementing ML models from scratch

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