Machine Learning Foundations: Code Projects

Repository for all my original code project submissions for UW CSE446: Machine Learning.

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These projects reflect my expertise within the following ML topics:

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Basics
Basic Probability and Linear Algebra
Maximum Likelihood Estimation
Convexity
Irreducible Error
Bias-Variance Trade-off

Regression
Linear Regression + Basis Functions
Gradient Descent and SGD
Regularization
Sparsity and Variable Selection

Classification
Classification
Logistic Regression
Kernels

Neural Networks
Neural Network Basics
Backpropagation
Convolutional Neural Networks
Recurrent Neural Networks
Long Short-Term Memory (LSTM)
Attention Mechanism

Unsupervised Learning
K-means
Gaussian Mixture Model (GMM)
Principal Component Analysis (PCA)
Singular Value Decomposition (SVD)
Matrix Completion
Auto-encoder