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

By: Ahmed Fawzy Gad (Author) , Fatima Ezzahra Jarmouni (Author)

Extended Catalogue

Ksh 27,300.00

Format: Paperback or Softback

ISBN-10: 0323909337

ISBN-13: 9780323909334

Publisher: Elsevier Science & Technology

Imprint: Academic Press Inc

Country of Manufacture: NL

Country of Publication: GB

Publication Date: Nov 26th, 2020

Publication Status: Active

Product extent: 300 Pages

Weight: 482.00 grams

Dimensions (height x width x thickness): 15.30 x 22.90 x 2.00 cms

Product Classification / Subject(s): Physiology
Science: general issues
Neurosciences

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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.

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