This Repository is a part of 100DaysofMLCode challenge
Check out the Jupyter Notebook here
Check out the project here
In this project, we will use a K-means algorithm to perform image classification. Clustering isn't limited to the consumer information and population sciences, it can be used for imagery analysis as well. Leveraging Scikit-learn and the MNIST dataset, we will investigate the use of K-means clustering for computer vision.
For this project, we will be using the MNIST dataset. It is available through keras, a deep learning library we have used in previous tutorials. Although we won't be using other features of keras today, it will save us time to import mnist from this library. It is also available through the tensorflow library or for download at http://yann.lecun.com/exdb/mnist/.