Model Validation - I
Explore the concept of model validation and its importance in deep learning to avoid overfitting. Learn how to split data for validation and apply validation_split in Keras. Understand how tuning hyperparameters impacts model accuracy through practical examples.
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Validation
The model performance on the training data is not a good indicator of how well the model will perform on the test data. For this, we should use the validation data to test the model’s performance.
Validation data is only held out from training and is only used to test the model’s performance.
The validation set checks overfitting and therefore eliminates errors that can be caused for future predictions and observations if an analysis corresponds too precisely to a specific dataset.
In ...