Physics-Informed Neural Networks (PINNs) transforming how we solve complex scientific and engineering problems. This book is your essential guide to understanding this powerful technique, which elegantly combines the flexibility of neural networks with the fundamental rigor of physical laws.   PINNs embed partial differential equations (PDEs) and their associated boundary and initial conditions directly into a neural network's training process via a custom loss function. This means the neural network itself learns to obey the laws of physics! The solution function becomes a neural...