Summary

In this chapter, we looked at a number of technologies that support the creation and use of neural networks.

We covered data presentation to an ANN, layers of an ANN, creating the model, gradient calculations for gradient descent algorithms, loss functions, and saving and restoring models. These topics are important precursors to the concepts and techniques that we will encounter in subsequent chapters when we develop neural network models.

Indeed, in the next chapter, we will start to use TensorFlow in earnest by exploring a number of supervised learning scenarios, including linear regression, logistic regression, and k-nearest neighbors.