DEEP LEARNING FOR MULTIPLE IMAGE CLASSIFICATION

In this project we build an image classifier with Keras and Convolutional Neural Networks for the Fashion MNIST dataset. This data set includes 10 labels of different clothing types with 28 by 28 grayscale images. There is a training set of 60,000 images and 10,000 test images.

Label	Description
0	    T-shirt/top
1	    Trouser
2	    Pullover
3	    Dress
4	    Coat
5	    Sandal
6	    Shirt
7	    Sneaker
8	    Bag
9	    Ankle boot

The Data

TASK 1: Run the code below to download the dataset using Keras.

from keras.datasets import fashion_mnist

(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()

Using TensorFlow backend.

Visualizing the Data

TASK 2: Use matplotlib to view an image from the data set. It can be any image from the data set.

import matplotlib.pyplot as plt