This repository contains my completed assignments for CS189: Machine Learning. Each assignment focuses on a different ML model/technique(eg: SVM, LDA/QDA, Neural Network), and contains both a math section where I derive important results and a coding section where I code these models from scratch. None of the models come from popular libraries
**** I'm not allowed to disclose my solutions publicly, however for employer requests, please email me @ [email protected]***
Homeworks in this repository:
HW1: Hard Margin SVM's, training techniques: K-Fold CrossValidation, Hyperparamter Tuning), Achieved 98.5 percent accuracy on SPAM Dataset
HW2: Probability Review, Multivariate Gaussians, Computing Gradients, Linear Algebra Review (No Coding, just deriving popular and important results and theorems)
HW3: Gaussian Classifiers(LDA, QDA), Covariance Matrices, Discriminant Functions
HW4: Logistic Regression, Newton's Method, Lasso, Ridge Regression(Achieved 99.4 percent on Wine Dataset)
HW5: Decision Trees, Bagging, Random Forests(Archived 83 percent on Spam(pretty bad))
HW6: Neural Networks, Convolutional Neural Networks, Pooling
HW7: