Introduction to Deep Learning and Neural Networks with Python™: A Practical Guide

Author: Gad, Ahmed Fawzy

Brand: Academic Press

Edition: 1

ISBN: 9780323909334

Release Date: 07-12-2020

Package Dimensions: 8.9 x 6.0 x 1.0 inches

Languages: English

Binding: paperback

Number Of Pages: 300

Details: 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