Parallelizing Neural Network Training with TensorFlow

In this chapter, we will move on from the mathematical foundations of machine learning and deep learning to focus on TensorFlow. TensorFlow is one of the most popular deep learning libraries currently available, and it lets us implement neural networks (NNs) much more efficiently than any of our previous NumPy implementations. In this chapter, we will start using TensorFlow and see how it brings significant benefits to training performance.

This chapter will begin the next stage of our journey into machine learning and deep learning, and we will explore the following topics:

• How TensorFlow improves training performance
• Working with TensorFlow's Dataset API (tf.data) to build input pipelines and efficient model training
• Working with TensorFlow to write optimized machine learning code
• Using TensorFlow high-level APIs to build a multilayer NN
• Choosing activation functions for artificial NNs
• Introducing...