From the course: Deep Learning: Image Recognition
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Challenge: Simple image classification - Python Tutorial
From the course: Deep Learning: Image Recognition
Challenge: Simple image classification
(bright upbeat music) - Well great. We have been creating the models. Simple, enhanced, and advanced. Now it's your turn. You will go ahead and work on a challenge, and in this challenge, we will take our enhanced CNN model from the previous lesson, and add another convolutional layer to deepen the network architecture. So, this exercise aims to help you understand how increasing the depth of the network can affect the model's performance and generalization. So, you will go ahead and modify the existing enhanced CNN model by adding an additional convolutional layer to it. You will then train the modified model on the CIFAR-10 dataset. Next, you will evaluate the model's performance and observe any improvements. Let's summarize the steps that you will be completing for this challenge. Number 1, you make sure that you import the necessary libraries. Number 2, load and pre-process the data. 3, modify the model. 4, compile and train the model. And 5, evaluate the model, and then finally…
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