Summary

In this chapter, you learned how to use TensorFlow, an open source library for numerical computations, with a special focus on deep learning. While TensorFlow is more inconvenient to use than NumPy, due to its additional complexity to support GPUs, it allows us to define and train large, multilayer NNs very efficiently.

Also, you learned about using the TensorFlow Keras API to build complex machine learning and NN models and run them efficiently. We explored model building in TensorFlow by defining a model from scratch via subclassing the tf.keras.Model class. Implementing models can be tedious when we have to program at the level of matrix-vector multiplications and define every detail of each operation. However, the advantage is that this allows us, as developers, to combine such basic operations and build more complex models. We then explored tf.keras.layers, which makes building NN models a lot easier than implementing them from scratch.

Finally, you learned about...