in python

$$ Data provided: dataset.csv

$$ Classes are in the last column.

$$ Use K$-$fold $=5$

$$ Design using tensorflow and keras

Procedure

$1.$ Design an MLP$-$perceptron and classify the assigned dataset using K$-$fold$=5$:

a$)$ Learning rate: $0\mathrm{.}1$

b$)$ Number of hidden layers: $4$

$$ Number of neurons per layer: $50$

$$ Activation function: Relu

c$)$ Hyperparameters

$$ optimizer $=$ SGD

$$ loss $=$ 'mse'

$$ metrics $=$ accuracy

$$ batch$\_$size $=64$

$$ Epoh $=5$

d$)$ Plot Accuracy vs Epoh $($X$-$axis: Epoh, Y$-$axis: Accuracy$)$

e$)$ Perform the test, that is$,$ the classification with the test data and print the accuracy

$2.$ now change the layout as follows

a$)$ Learning rate: $0\mathrm{.}01$

b$)$ Number of hidden layers: $6$

$$ Number of neurons per layer: $60$

$$ Activation function: Relu

c$)$ Hyperparameters

$$ optimizer $=$ Adam

$$ loss $=$ 'binary$\_$crossentropy'

$$ metrrics $=$accuracy$$

$$ batch$\_$size $=128$

$$ Epoh $=5$

d$)$ Plot Accuracy vs Epoh $($X$-$axis: Epoh, Y$-$axis: Accuracy$)$

e$)$ Perform the test after training and print the accuracy