gladwinyjh / ML-Basics

ML algorithms from scratch

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ML-Basics

ML algorithms mostly from scratch to strengthen my understanding of concepts.

Notes + Implementation (code) of ML concepts learned from Dr. Kilian Weinberger and others from books and the web.

Github notebook viewer is not always too kind with math equations, so it is best viewed with an alternative notebook viewer, like nbviewer.

Topics Covered thus far

Linear, Logistic Regression

Linear Regression Logistic Regression


K-nearest neighbors

KNN


Perceptron

Perceptron


Naive Bayes

Gaussian Naive Bayes


Support Vector Machines

Soft Margin SVM Soft Margin SVM RBF


Decision Trees / CART

Classification Tree

Regression Tree


K-means, K-means++

K-means K-means++


Feed Forward Neural Network

FFN


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ML algorithms from scratch

License:MIT License


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Language:Jupyter Notebook 100.0%