Neural Networks and Deep Learning
In this chapter, we will discuss neural networks (NNs) in machine learning (ML), often referred to as artificial NNs or ANNs. We will introduce many important topics in this field of science, including fundamental concepts that led to the development of ANNs, and relevant use cases for their application. At this point, it’s important to note that the term deep learning (DL) refers to ML that is implemented with the use of deep NNs (DNNs). We will explain the term “DNN” later in this chapter.
We will also introduce some tools and frameworks that make it easier for us to create NNs, such as TensorFlow and Keras, and we will use those tools to build an NN in our hands-on activities later in this chapter. Finally, we will expand the discussion to include different types of NN architectures, common challenges in NN implementations, and some practices for optimizing our NN architectures.
As a side note, I first started learning...
