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Machine Learning Practice

The purpose of this repo is to practice implementing machine learning algorithms both from scratch, and with more efficient modules. I plan on really digging deep into the thoery, and implementing it in real-life data.

Below are the projects being worked on. These mirror projects assigned in the Cornell course "Machine Learning for Intelligent Systems" (CS 4780/CS 5780), except I alter the projects just a bit, and explore a bit deeper.

  1. Euclidean Distance

1. K-Nearest Neighbors

2. Perceptron

2. Naive Bayes

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