Description

Introduction to Deep Learning and Neural Networks with Python™: 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 book’s 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.

   Examines the practical side of deep learning and neural networks
   Provides a problem-based approach to building artificial neural networks using real data
   Describes Python™ functions and features for neuroscientists
   Uses a careful tutorial approach to describe implementation of neural networks in Python™
   Features math and code examples (via companion website) with helpful instructions for easy implementation

Book Details

   Language: English
   Published: 2020
   ASIN: B08P75B9C4
   Format: True EPUB