Description
Simulation By Deep Neural Operator (DeepONets), the simulation training course by Deep Neural Operator has been published by Yudemy Academy. This comprehensive course is designed to equip you with the skills to effectively use simulations by deep neural operators. We cover the fundamental concepts of solving partial differential equations (PDEs) and show how to implement a simulation code through the application of a deep operator network (DeepONet) using data generated by solving PDEs by the finite difference method (FDM). let’s make This comprehensive course provides a thorough understanding of machine learning and fundamental aspects of partial differential equations, PDEs, and simulation by deep neural operators using the Deep Operator Network (DeepONet).
What you will learn
- Understand the theory behind deep neural operator equation solvers.
- Construction of deep neural operator solver based on DeepONet.
Build a deep neural operator code using DeepXDE. - Build a deep neural operator code using Pytorch.
Who is this course suitable for?
- Engineers and programmers who want to learn simulation through a deep neural operator
Specifications of the course Simulation By Deep Neural Operator (DeepONets)
- Publisher: Udemy
- teacher : Dr. Mohammad Samara
- English language
- Education level: all levels
- Number of courses: 36
- Training duration: 8 hours and 28 minutes
Chapters of Simulation By Deep Neural Operator (DeepONets) course
Course prerequisites
- High School Math
- Basic Python knowledge
Pictures
Sample video
Installation guide
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Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
10.98 GB
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