Introduction to Deep Learning and Neural Networks with Pythonâ¢: A Practical Guide
is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks.
Providing math and Python⢠code examples to clarify neural network calculations, by bookâs end readers will fully understand how neural networks work starting from the simplest model Y=X and building from scratch.
Details and explanations are provided on how a generic gradient descent algorithm works based on mathematical and Python⢠examples, teaching you how to use the gradient descent algorithm to manually perform all calculations in both the forward and backward passes of training a neural network.
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