Write a Python program for applying CNN with considering the following requirements:Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train )Select 2500 images and you must ensure that each class must contain at least 180 samplesApply CNN that keeps noisy examples. Overall, the pseudocode of CNN is as follows:The code must contain at least one lambda expressionThe code must contain at one comprehension listIt is Not allowed to use the numpy library.Euclidean distance is the distance between two samples in Euclidean space. The formula can be expressed as: + X Python Tryit EditorW X Python Tryit EditorW X Python OperatorsX Answered: You rece bX CSC 605_HW1 - Jup EX Downloads/csc/flocalhost:8888/notebooks/Downloads/csc/CSC%20605_HW1.ipynb#2)-Convert-the-following-function-to-lambda-expression O->قائمة القراءةSQL for Beginners:. ûB مرحبّار فياض - . .BlackGoogle hiljs AYouTubeGmail Mالتطبيقاتقائمة القراءةCjupyter CSC .•_HW' Last Checkpoint: ácll io uual (autosaved)LogoutFileEditViewInsertCellKernelWidgetsHelpPython 3 ONot Trusted+RunMarkdownCondensed Nearest Neighbor (CNN)Data reduction techniques aim to simplify the training data by removing noisy and redundant data, so that, machine learning algorithms can learn faster withlittle or no performance degradation, as if the entire training set T is used.CNN was the first data reduction Algorithm. This algorithm is an incremental method that starts with adding one example of each class to the subset Srandomly from training set T. Then, for each example x in T is classified using the examples in S. if the example x is incorrectly classified, it will be added toS. This guarantees all instances in T are classified correctly. Based on this criterion, noisy examples will be retained because they are commonly classifiedwrongly by their k – NN (whrere k = 1)The CIFAR-10 dataset The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 trainingimages and 10000 test images.In order to load CIFAR-10 dataset, First, download tensorflow library using the following command:install tensorflowThen, use the following code:In [63]: import tensorflowimport cv2from tensorflow import kerasfrom PIL import Imageimport numpy as p(x_train, y_train), (_, _) = tf.keras.datasets.cifar10.load_data()x_train = [cv2.cvtColor(image, cv2.COLOR_BGR2GRAY).flatten().tolist() for image in x_train]##x_train=np.asarray(x_train)print(len(x_train))print(len(x_train[0])) # 32*325000010243:03 PMO Type here to search96°FO C 1) ENG9/27/2021() + X Python Tryit EditorW X Python Tryit EditorW X Python OperatorsX Answered: You rece bX CSC 605_HW1 - Jup EX Downloads/csc/flocalhost:8888/notebooks/Downloads/csc/CSC%20605_HW1.ipynb#2)-Convert-the-following-function-to-lambda-expression O->قائمة القراءةSQL for Beginners:. ûB مرحبّار فياض - . .BlackGoogle hiljs AYouTubeGmail MالتطبيقاتCjupyter CSC 1.•_HW) Last Checkpoint:r ácldl io uual (autosaved)LogoutWidgetsPython 3 OFileEditViewInsertCellKernelHelpNot Trusted+RunMarkdown1024Write a Python program for applying CNN with considering the following requirements:• Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train )• Select 2500 images and you must ensure that each class must contain at least 180 samples• Apply CNN that keeps noisy examples. Overall, the pseudocode of CNN is as follows:PROCEDURE CNN(S,D,Z)BEGINZ := {};REPEATadditions:=FALSE;FOR all patterns in the training set DORandomly pick æ from training set, SFind z. E Z such that D(x, zc) = min; D(x, z;)IF class(x) # class(zc) THENZ := Z U x;additions:=TRUEEND IF3:06 PMO Type here to search96°FO G ») ENG9/27/2021()

# import pandas as pdimport pandas as pdimport randomimport math # reading training datadata =…

Answered: Write a Python program for applying CNN…

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE