9.15 GB | 00:27:42 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Introduction (54.46 MB)
2 Installing Anaconda (123.45 MB)
3 Course Structure (170.75 MB)
3 2 Physics Informed Neural Networks (PINNs) (3.83 MB)
1 Deep Learning Theory (181.46 MB)
2 PyTorch Tensors Basics (418.05 MB)
3 Tensors to NumPy arrays (184.92 MB)
4 Backpropagation Theory (375.74 MB)
5 Backpropagation using PyTorch (131.45 MB)
1 Numerical solution theory (279.24 MB)
2 Pre-processing (364.35 MB)
3 Solving the Equation (234.75 MB)
4 Post-processing (108.59 MB)
1 Pre-processing (534.99 MB)
2 Solving the Equation (207.81 MB)
3 Post-processing (145.75 MB)
1 PINNs Theory (186.62 MB)
2 Define the Neural Network (239.74 MB)
3 Initial Conditions and Boundary Conditions (526.38 MB)
4 Loss Function (397.27 MB)
5 Train the Model (260.68 MB)
6 Optimizer (140.68 MB)
7 Results Evaluation (197.01 MB)
1 Define the Neural Network (203.54 MB)
2 Initial Conditions and Boundary Conditions (335.74 MB)
3 Optimizer (269.04 MB)
4 Loss Function (365.76 MB)
5 Train the Model (84.21 MB)
6 Results Evaluation (185.93 MB)
1 Set Geometry, B C and I C (615.6 MB)
2 Define the Network and the PDE (219.78 MB)
3 Train the model (127.56 MB)
4 Result evaluation (55.76 MB)
1 Set Geometry (277.49 MB)
2 Set Boundary Conditions (396.92 MB)
3 Define the Network and the PDE (414.37 MB)
4 Train the model (110.65 MB)
5 Result evaluation (215.81 MB)
Screenshot
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