In this chapter, we will explain some basic concepts of Machine Learning (ML) and Deep Learning (DL) that will be used in all subsequent chapters. We will start with a brief introduction to ML. Then we will move on to DL, which is one of the emerging branches of ML.
We will briefly discuss some of the most well-known and widely used neural network architectures. Next, we will look at various features of deep learning frameworks and libraries. Then we will see how to prepare a programming environment, before moving on to coding with some open source, deep learning libraries such as DeepLearning4J (DL4J).
Then we will solve a very famous ML problem: the Titanic survival prediction. For this, we will use an ...
