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
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
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Write a Python
- 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
![+
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pip install tensorflow
Then, use the following code:
In [63]: 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[e])) # 32*32
<IPython.core.display.Javascript object>
50000
1024
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
11:14 PM
P Type here to search
87°F A O O
DG 4) ENG
9/27/2021](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc3602a5e-74b9-44cf-9eb8-9dd4a68cc73f%2F116b77e7-b580-4c6a-b68a-08ba88a01e19%2Fo7txixf_processed.png&w=3840&q=75)
Transcribed Image Text:+
و مترجم - بحث Go ogle
X Untitled4 - Jupyter Noteb
x CSC 605_HW1 - Jupyter N
X Downloads/csc/
O x Answered: Write a Python b
localhost:8888/notebooks/Downloads/csc/CSC%20605_HW1.ipynb O
قائمة القراءة
| bartleby b sQL for Beginners. û Black. - jolyó li>yo B Google biljs A YouTube
Gmail M Släuhill
jupyter cSC 1.°_HW' Last Checkpoint: :rio l dio ual (autosaved)
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Python 3 O
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pip install tensorflow
Then, use the following code:
In [63]: 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[e])) # 32*32
<IPython.core.display.Javascript object>
50000
1024
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
11:14 PM
P Type here to search
87°F A O O
DG 4) ENG
9/27/2021
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