ML-from-scratch

Machine Learning materials and projects for the machine learning course at sharif university of technology

Table of contents

Ensemble methods

Bagging\
Random Forest\
Boosting : AdaBoost\
Feature Selction

>Filtering : correlation coefficient

KNN_Decision tree
k nearest neighbour \
decision tree\
training models and t-test for comparing them

>using k fold validation for evaluation

PCA kmeans GMM
K-Means\
gaussian mixture model \
t-sne\
PCA

implementing PCA using SVD\
implementing PCA without using SVD

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SVM_perceptron
soft margin SVM\
Perceptron