Deep Learning from Scratch: Building with Python from First Principles

Deep Learning from Scratch: Building with Python from First Principles Front Cover
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2019-09-24
252 pages

Book Description

With the resurgence of neural in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.

Author Seth Weidman shows you how neural networks work using a first approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning .

This book provides:

  • Extremely clear and thorough mental models—accompanied by working examples and mathematical explanations—for understanding neural networks
  • Methods for implementing multilayer neural networks from scratch, using an easy-to-understand framework
  • Working implementations and clear-cut explanations of convolutional and recurrent neural networks
  • Implementation of these neural concepts using the popular PyTorch framework

Book Details

  • Title: Deep Learning from Scratch: Building with Python from First Principles
  • Author:
  • Length: 252 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2019-09-24
  • ISBN-10: 1492041416
  • ISBN-13: 9781492041412