What is the significance of understanding the mechanics inside the training process of a convolutional neural network?
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Extending to Multiple Filters

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1.
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3 mins • 1 pt
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2.
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3 mins • 1 pt
Explain how the derivative of the loss function is computed with respect to the entries of CIJ.
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3.
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3 mins • 1 pt
Describe the impact of a particular entry UV on the loss function L.
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4.
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What is the role of the chain rule in understanding how L is impacted by a particular entry CIJ?
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5.
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How does the ReLU activation function affect the derivative of CIJ with respect to KUV?
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6.
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What is the process of updating parameters using the derivatives obtained from the loss function?
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7.
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In what way can the knowledge gained from this simple example be extended to deeper neural networks?
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