Saving and Loading Machine Learning Models with Keras: A Comprehensive Guide

Saving and Loading Machine Learning Models with Keras: A Comprehensive Guide💾🔄🔃🚀

Why save models?* Save time by avoiding the need to retrain each time
* Use optimized weights and biases for predictions

How to save a model in Keras1. Choose a name for your model
2. Callmodel.save()with the file name as an argument

When to save a model* After training completion
* Using callbacks to save at each epoch

Loading a saved model in Keras1. Useload_model()and provide the file name

Using Callbacks for optimization*ModelCheckpoint: Save the best performing model
*EarlyStopping: Interrupt training if no progress on validation set score

Optimizing performance with Early Stopping1. Set a large number of epochs to train
2. Monitor validation scores
3. Stop training when no improvement is observed for a certain period (patience)

Example: Training, saving, and loading a model with Keras...