Function Approximation with Neural Networks

For this e-book I recommend reading the e-book Universal Approximation Theorem from this website. Here we will show examples of how to approximate functions of various nature as well as find solutions to differential equations. The subsections dealt with will have a I, II or III, this for functions with a domain in 1, 2 or 3 dimensions respectively.

📄️ Sinuoidal Functions I

For the examples, we will use the following libraries,

📄️ Sinuoidal Functions II

We will continue with sinusoidal type functions for the examples we will present, but now from $\mathbb^2\to\mathbb{R}$. For the examples, we will use the following libraries,

📄️ Some Comments

As you can see, until now, all the experiments done on the sinusoidal functions do not rigorously approximate the proposed functions, but this has several purposes.