If you want to perform simulation.
With artificial neural networks, then we need pens and pens is a method that is going to solve pdes.
Or partial differential equations.
So what is Pence?
Pence stands for Physics Informed Neural Networks.
They are a class of machine learning models that combine artificial neural networks with principles
of physics to solve partial differential equations or pdes and other physical problems.
Pdes are used in scientific computing and engineering to approximate and solve complex physics or physical
systems such as fluid dynamics, heat transfer and structural mechanics.
The key idea behind pens is to train a neural network to approximate the solution of pdes while enforcing
the governing physics equation as constraints during training.
In this class, we are going to learn how to solve these pins, using or starting from learning how
to solve or how to write code to solve a pdes using finite difference method.
After that we are going to use PyTorch to well solve pdes using pens.
What we will find is writing code with pytorch is quite heavy, so we will try to fasten the process
of developing a pens code by learning deep library in which will be or will save us some time to model
a physical system.
Hope this class will be your or the best class for you to be prepared to learn pens and in general even
how to deal with partial differential equations and solve them numerically.
Hope you the best in your endeavor and let's learn together pens and understand the code and get the
skills to write such two to solve this problems.