Compare the Accuracy of Parmeteric model with NON Parameteric Model by performing following

$2\mathrm{.}1$ Apply a non parameteric model such as KNN or Decision Tree using python for the classification, you should be able to define the training, testing and validation test, mention the pre$-$processing steps required for your data set $.$ Find the accuracy of the clasess using Confusin matric and Accuracey curve etc.

$2\mathrm{.}2$ Appy a parameteric model such ANN using Python Jupyter Notebook to classify using one of the following data set. $,$ mention the pre$-$processing steps required for your data set. Use $4-$fold cross validation for training, testing and validating the neural network. Describe how you built the artificial neural network in Python Notebook such as How many neurons$/$layers are in the network? Why? How did you configure the initial weights Compare the Accuracy of the ANN model with the accuracy of non paramertric model as found in the above task $3\mathrm{.}0$

$2\mathrm{.}3$Develeop a Convolutation Neural network Model and compare its accuracy with ANN. Highlight which of the models performed best among all the models you used.