Deep Learning - Crash Course 2023 - Visualize the Accuracy with Epochs

The video tutorial explains how increasing the number of epochs can affect model accuracy. It demonstrates how to modify code to store the best accuracy and parameters. The concept of learning rate is introduced to reduce oscillations in accuracy. Hyperparameter tuning is discussed as a method to optimize model performance. Finally, the tutorial covers testing the model with determined parameters and concludes with an introduction to sigmoid neurons.

What is the effect of increasing the number of epochs on the accuracy of the model?

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Explain how the accuracy score changes with each iteration in the training process.

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What modifications are made to store the best possible accuracy during training?

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How does the learning rate affect the convergence of the model?

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What is hyperparameter tuning and why is it important in deep learning models?

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Describe the impact of different learning rates on the accuracy and number of iterations required.

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What was the accuracy score achieved on the test model after applying the determined parameters?

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