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-# Learn and use machine learning
-
-This notebook collection is inspired by the book
-*[Deep Learning with Python](https://books.google.com/books?id=Yo3CAQAACAAJ)*.
-These tutorials use `tf.keras`, TensorFlow's high-level Python API for building
-and training deep learning models. To learn more about using Keras with
-TensorFlow, see the [TensorFlow Keras Guide](../../guide/keras).
-
-Publisher's note: *Deep Learning with Python* introduces the field of deep
-learning using the Python language and the powerful Keras library. Written by
-Keras creator and Google AI researcher François Chollet, this book builds your
-understanding through intuitive explanations and practical examples.
-
-To learn about machine learning fundamentals and concepts, consider taking the
-[Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course/).
-Additional TensorFlow and machine learning resources are listed in [next steps](../next_steps).
-
-1. [Basic classification](./basic_classification)
-2. [Text classification](./basic_text_classification)
-3. [Regression](./basic_regression)
-4. [Overfitting and underfitting](./overfit_and_underfit)
-5. [Save and restore models](./save_and_restore_models)