Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

KNN Implementation in Java

Stock market analsis with python tools

Scripts for machine learning algorithms in MATLAB/Octave and python

Knn algorithm proof of concept

1-hour ML introduction for colleagues at TrueBlue. KNN and fashion-mnist will be ran by every participant on their laptop, then overview of the dog project and finally an explanation of kernel and how they extract information from images