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If you want to perform simulation.

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With artificial neural networks, then we need pens and pens is a method that is going to solve pdes.

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Or partial differential equations.

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So what is Pence?

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Pence stands for Physics Informed Neural Networks.

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They are a class of machine learning models that combine artificial neural networks with principles

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of physics to solve partial differential equations or pdes and other physical problems.

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Pdes are used in scientific computing and engineering to approximate and solve complex physics or physical

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systems such as fluid dynamics, heat transfer and structural mechanics.

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The key idea behind pens is to train a neural network to approximate the solution of pdes while enforcing

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the governing physics equation as constraints during training.

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In this class, we are going to learn how to solve these pins, using or starting from learning how

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to solve or how to write code to solve a pdes using finite difference method.

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After that we are going to use PyTorch to well solve pdes using pens.

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What we will find is writing code with pytorch is quite heavy, so we will try to fasten the process

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of developing a pens code by learning deep library in which will be or will save us some time to model

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a physical system.

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Hope this class will be your or the best class for you to be prepared to learn pens and in general even

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how to deal with partial differential equations and solve them numerically.

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Hope you the best in your endeavor and let's learn together pens and understand the code and get the

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skills to write such two to solve this problems.