Need help with the a code Description

The project shall do the following:

The following neural networks will be used:

$1.$ MLP $("$Multi$-$Layer Perceptron"$)$

$2.$ CNN $($Convolutional Neural Network$)$

$3.$ Hybrid: combination MLP$,$ CNN$,$ RNN $("$Recursive Neural Network"$)$

Class balancing will be done using the Borderline$-$Smote method.

Metodolog$$a

$1.$ Part$-1-$ Pre$-$processing:

For each assigned neural network $($MLP$,$ Hybrid, CNN$),$ use data from a $1$ patient and do the following:

$1\mathrm{.}1.$ Perform classification using "Raw data", class balancing using the Borderline Smote method and CV$=6$

$1\mathrm{.}2.$ Perform Classification with StandardScaler, Normalized, Class Balancing, and CV $=6$ Data

$1\mathrm{.}4.$ Get the best Hyper$-$parameters $($learning rate, bactch$\_$size, epoch, etc.$)$ by doing various tests or using GridSearch to get the highest accuracy.

The result of the classification with the neural networks must have an accuracy $("$Acurracy$")$ greater than $70\%.$