Deep Learning - Crash Course 2023 - Training the Neural Network

The video tutorial covers the process of importing necessary libraries and setting up a 2D classification dataset. It explains how to split the dataset into training and test sets, and how to prepare a deep learning model by adjusting the input shape to match the dataset's features. The model is defined with two hidden layers and compiled using the RMSprop optimizer. The training process is demonstrated over 1000 epochs, showing improvements in accuracy and reductions in loss. The video concludes with a summary of the model's performance and hints at future learning topics.

What optimizer is used in the model compilation, and why is it significant?

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What were the training and validation accuracies achieved at the end of the training?

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Summarize the key steps taken in the video to define and train the model.

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