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:USE THIS CODE 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*32NOTE: PLEAS USE THE CODE I ATTACHED THANK YOU + xGoogle u - G X Untitled4 - Jupyter NotebeX CSC 605_HW1 - Jupyter NX Downloads/csc/C X Answered: Write a Python blocalhost:8888/notebooks/Downloads/csc/CSC%20605_HW1.ipynb O->fقائمة القراءة| bartlebySQL for Beginners:. ûB مرحبّا, فياض - ..BlackGoogle hiljs AYouTubeGmail MالتطبيقاتCjupyter CSC 1._HW) Last Checkpoint: ) :. Y delul die ws (autosaved)LogoutFileEditViewInsertCellKernelWidgetsHelpNot TrustedPython 3 O+RunMarkdownpip 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[@])) # 32*32500001024Write 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 samples11:14 PMO Type here to search87°FD G ») ENG9/27/2021

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Computer Networking: A Top-Down Approach (7th Edition)

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Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

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Question

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 samples
Apply CNN that keeps noisy examples. Overall, the pseudocode of CNN is as follows:
- The code must contain at least one lambda expression
- The code must contain at one comprehension list
- It 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:

USE THIS CODE

import tensorflow
import cv2
from tensorflow import keras
from PIL import Image
import 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*32

NOTE: PLEAS USE THE CODE I ATTACHED

THANK YOU