Question: Python G Assignment 1 | assignments Weig... wandb.ai Question 1 (2 Marks) Download the fashion-MNIST dataset and plot 1 sample image for each class as

Python G Assignment 1 | assignments Weig... wandb.ai Question 1 (2

Marks) Download the fashion-MNIST dataset and plot 1 sample image for each

class as shown in the grid below. Use "from keras.datasets import fashion_mnist"

Python

G Assignment 1 | assignments Weig... wandb.ai Question 1 (2 Marks) Download the fashion-MNIST dataset and plot 1 sample image for each class as shown in the grid below. Use "from keras.datasets import fashion_mnist" for getting the fashion mnist dataset. IO examples whol... lem... kind... polis... apric... absu... dark... prim... hap... lyric-... wan... fine-... sple... ethe... driv... reviv... CONOCNE DODON ULOUS stell... fresh... eart... twili... stell... COS... ethe... magi... bree... vital... treas... Sweep: zwztbeow 1 189 TIL O wandb.ai Question 2 (10 Marks) Implement a feedforward neural network which takes images from the fashion-mnist data as input and outputs a probability distribution over the 10 classes. Your code should be flexible so that it is easy to change the number of hidden layers and the number of neurons in each hidden layer. We will check the code for implementation and ease of use. Question 3 (18 Marks) Implement the backpropagation algorithm with support for the following optimisation functions sgd TIL O

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