/Machine_Learning_CS_5783

Python based machine learning codes developed for CS_5783 course

Primary LanguagePython

Python Codes Developed as part of Machine_Learning_CS_5783 course

Assignments

  1. HW1--Linear Classifiers:

    1. KD tree (data structure).
    2. Trainig data set using customised 2D multivariate Gaussian distributions.
    3. Maximum-likelihood linear least squares classifier.
    4. Nearest neighbors classification using KD tree.
    5. Testing above both classifier using overlapped Gaussian distributions.

  2. HW2--Bayes Classifiers:

    1. Naive Bayes (uniform Dirichlet prior) on MNIST data set.
    2. Naive Bayes (Gaussian kernel) and ROC curve (FPR vd TPR).
    3. Brute force nearest neighbors search (no KD tree).

  3. HW3--Regression on NHSA automobile crash test data:

    1. Linear regression: polynomial basis functions.
    2. Linear regression: radial basis functions.
    3. Bayesian MAP estimates.
    4. Logistic regression on Iris dataset

  4. HW4:

    1. Gaussian process regression with five-fold cross-validation.
    2. K-means clustering.
    3. Hidden Markov Models (forward-backward algorithm).