Copyright 2018 The TensorFlow Authors.¶ #@title Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Image classification
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:
Examine and understand data Build an input pipeline Build the model Train the model Test the model 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.