In this lesson, we will cover the basics of neural networks and how to set up a deep learning programming environment. We will also explore the common components of a neural network and its essential operations. We will conclude this lesson by exploring a trained neural network created using TensorFlow.

This lesson is about understanding what neural networks can do. We will not cover mathematical concepts underlying deep learning algorithms, but will instead describe the essential pieces that make a deep learning system. We will also look at examples where neural networks have been used to solve real-world problems.

This lesson will give you a practical intuition on how to engineer systems that use neural networks to solve problems—including how to determine if a given problem can be solved at all with such algorithms. At its core, this lesson challenges you to think about your problem as a mathematical representation of ideas. By the end of this lesson, you will be able to think about a problem as a collection of these representations and then start to recognize how these representations may be learned by deep learning algorithms.