Machine-Learning-Course-Assignments

Assignment 1: Linear Algebra for Machine Learning

• Matrix Transformation
  • Notebook Link
• Eigen Decomposition
  • Decomposition and reconstruction of invertible and invertible symmetric matrices

• Singular Value Decomposition
  • Reconstructing a book cover image using singular value decomposition with varying ranks

Assignment 2: Logistic Regression and Adaboost for Classification

• Data Preprocessing

- Telco Customer Churn Notebook

- Census Income Train Notebook, Census Income Test Notebook

- Credit Card Fraud Notebook

• Adaboost with Logistic Regression from Scratch
  • Python Code
• Results and Discussion
  • Report Link

Assignment 3: Feed Forward Neural Network from Scratch

• Layer Abstractions (Dense, ReLU, Softmax, Dropout) with Forward and Backward Propagations: Neural Network Backbone Code

• Loss function, Evaluation Metric, Loading, Preprocessing, Training, Evaluation and Plotting: Training Code

• Inference: Testing Code
• Report Link

Assignment 4: Expectation-Maximization (EM) Algorithm with Gaussian Mixture Models (GMM)

• Principal Component Analysis (PCA), Expectation-Maximization Algorithm, Log-likelihood Calculation: Python Code