airplane automobile bird cat deer dog frog horse ship truck Figure 1: CIFAR-10 Dataset. Given the CIFAR10 dataset, implement the following networks and report the results of the test accuracy via screenshot. Make sure to provide necessary comments on your code. The dataset can be loaded from here: COLAB LINK HERE (a) Implement the following deep learning architecture and evaluate its test accuracy. network models. Sequential() network.add(layers. Dense (128, activation=' network.add(layers. Dense (64, activation='sigmoid')) network.add(layers.Dense(10, activation='sigmoid')) = 'sigmoid')) network.compile (optimizer='sgd',loss='mse', metrics=['accuracy']) network.fit (X_train, y_train, epochs=20, batch_size=16) (b) Given that you are able to change the number of layers, number of neurons, activaiton functions, and the optimizer. Design your own architecture, provide your models code, and a screenshot of the highest test accuracy of your model. activation : [’sigmoid’, tanh’, ’relu] optimzer : ['sgd', 'RMSprop', 'Adam'] (c) Provide a high-level description of your model. Moreover, what components had the biggest impact on your accuracy?
airplane automobile bird cat deer dog frog horse ship truck Figure 1: CIFAR-10 Dataset. Given the CIFAR10 dataset, implement the following networks and report the results of the test accuracy via screenshot. Make sure to provide necessary comments on your code. The dataset can be loaded from here: COLAB LINK HERE (a) Implement the following deep learning architecture and evaluate its test accuracy. network models. Sequential() network.add(layers. Dense (128, activation=' network.add(layers. Dense (64, activation='sigmoid')) network.add(layers.Dense(10, activation='sigmoid')) = 'sigmoid')) network.compile (optimizer='sgd',loss='mse', metrics=['accuracy']) network.fit (X_train, y_train, epochs=20, batch_size=16) (b) Given that you are able to change the number of layers, number of neurons, activaiton functions, and the optimizer. Design your own architecture, provide your models code, and a screenshot of the highest test accuracy of your model. activation : [’sigmoid’, tanh’, ’relu] optimzer : ['sgd', 'RMSprop', 'Adam'] (c) Provide a high-level description of your model. Moreover, what components had the biggest impact on your accuracy?
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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use python and add comments on every line
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Step 1
In the code below, we first import the necessary libraries including Keras, layers, and models. We then load the CIFAR-10 dataset into two sets, training and testing.
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