This section familiarizes the reader with the basics of operating neural networks, how to select appropriate data, normalize features, and execute a data processing pipeline from scratch. Readers will learn how to pair ideal hyperparameters with appropriate activation, loss functions, and optimizers. Once completed, readers will have experienced working with real-world data to architect and test deep learning models on the most prominent frameworks.
This section comprises the following chapters:
- Chapter 1, Overview of Neural Networks
- Chapter 2, Deeper Dive into Neural Networks
- Chapter 3, Signal Processing – Data Analysis with Neural Networks
