© Rahul Bhalley 2021
R. BhalleyDeep Learning with Swift for TensorFlowhttps://doi.org/10.1007/978-1-4842-6330-3_5

5. Neural Networks

Rahul Bhalley1  
Ludhiana, India

I like nonsense; it wakes up my brain cells.

—Dr. Seuss

This chapter covers the basics of neural networks, a.k.a. deep learning. We discuss various foundational topics as follows: gradient-based optimization of input and parameters of the function (Section 5.1), linear models (Section 5.2), deep and dense neural network (Section 5.3), activation functions (Section 5.4), loss functions (Section 5.5), and optimization (Section 5.6) and regularization (Section 5.7) techniques. Finally, we summarize the chapter in Section 5.8.

5.1 Gradient-Based Optimization

In this section, we introduce ...

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