Classification using RNN-LSTM

This tutorial shows how to classify images of flowers using a tf.keras.Sequential model and load data using tf.keras.utils.image_dataset_from_directory. It demonstrates the following concepts:

• Efficiently loading a dataset off disk.
• Identifying overfitting and applying techniques to mitigate it, including data augmentation and dropout.

This tutorial follows a basic machine learning workflow:

1. Examine and understand data
2. Build an input pipeline
3. Build the model
4. Train the model
5. Test the model
6. Improve the model and repeat the process

In addition, the notebook demonstrates how to convert a saved model to a TensorFlow Lite model for on-device machine learning on mobile, embedded, and IoT devices.