K-Means (Lloyd's Methos) using MATLAB

K-means with error while creating some centroid haha

Developed Model to detect handwritten digits. Model is trained on MNIST data set, and 10 clusters are achieved as expected.

There are three parts in total.First, Use the data to do K‐means clustering implementation.Second,try some methods to predict Kobe Bryant’s shot type and write report.Third,try some methods to predict commentary star and write report.

Simple to use KMeans Java library.

Clustering the customers using an unsupervised machine learning approach.

Implementation of K Mean Clustering Algorithm

A Machine Learning algorithm that assigns the data of a given dataset to a number of clusters.

: Finding interesting trends/behaviors.

basic-ml-datasets-Some ml-datasets to practice different ml techniques.

This is Basic K-mean Clustering Example

k-means python implementation

An implementation of modified K-Means clustering on Biological Data (Proteins).

A website made using HTML, CSS, Bootstrap and Flask to recommend anime. We used KNN and K-Means algorithms to generate the recommendations.

The thing of beauty in baseball is that each year we have a chance to see players making a leap. Like Jose Bautista, Jose Ramirez, Ben Zobrist, etc. This research aims to find out of these breakout players, the improvement of what stats are more responsible for their WAR and wRC+ gain.

IBM Data Science Course - Data science notebook that clusters neighborhoods of Toronto based on the nearby venues that were extracted using the foursquare API.

This is a basic implementation of K-mean clustering algorithm in python

This repository consits of different Data Science projects