Overview of Neural Networks

Greetings to you, fellow sentient being; welcome to our exciting journey. The journey itself is to understand the concepts and inner workings behind an elusively powerful computing paradigm: the artificial neural network (ANN). While this notion has been around for almost half a century, the ideas accredited to its birth (such as what an agent is, or how an agent may learn from its surroundings), date back to Aristotelian times, and perhaps even to the dawn of civilization itself. Unfortunately, people in the time of Aristotle were not blessed with the ubiquity of big data, or the speeds of Graphical Processing Unit (GPU)-accelerated and massively parallelized computing, which today open up some very promising avenues for us. We now live in an era where the majority of our species has access to the building blocks and tools required to assemble artificially-intelligent systems. While covering the entire developmental timeline that brings us here today is slightly beyond the scope of this book, we will attempt to briefly summarize some pivotal concepts and ideas that will help us think intuitively about our problem here.

In this chapter, we will cover the following topics:

• Defining our goal
• Knowing our tools
• Understanding neural networks
• Observing the brain
• Information modeling and functional representations
• Some fundamental refreshers in data science