Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization

Cover of Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization by Brett Koonce
Author: Brett Koonce
Publisher: Apress
Year: 2021
Language: en
Edition: 1st ed.
Pages: 245
ISBN-13: 9781484261675
Dimensions:
Height: 9.25 Inches
Length: 6.1 Inches
Weight: 0.84 Pounds
Width: 0.61 Inches
Dewey Decimal: 006.32
Editorial overview Touché

Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization by Brett Koonce, published by Apress on January 5, 2021, is a comprehensive guide that explores practical machine learning and dataset categorization techniques. This 1st edition, comprising 245 pages, focuses on utilizing convolutional neural networks for image recognition through the Swift programming language, making complex concepts accessible to readers familiar with Swift.

Readers will find a structured approach that begins with an overview of machine learning and progresses to advanced topics such as neural networks and convolutions. The book covers essential techniques like data augmentation and training large networks, including cloud-based solutions, while also addressing the deployment of these systems on mobile devices. With a focus on categorizing various datasets, including greyscale data and larger datasets like imagenet, this resource serves as a practical introduction to artificial intelligence and programming within the context of modern operating systems.


Official synopsis Publisher

Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language.

It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you’ll perform data augmentation, build and train large networks, and build networks for mobile devices. You’ll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet.

Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field.

What You’ll Learn

  • Categorize and augment datasets
  • Build and train large networks, including via cloud solutions
  • Deploy complex systems to mobile devices

Who This Book Is For
Developers with Swift programming experience who would like to learn convolutional neural networks by example using Swift for Tensorflow as a starting point.

FAQ
What is “Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization” about?
This page includes the available description and bibliographic details for “Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization” by Brett Koonce. Synopsis preview: Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar a…
Who is the author of “Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization”?
“Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization” is credited to Brett Koonce.
When was “Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization” published?
Publisher: Apress. Year: 2021.
What is the ISBN for “Convolutional Neural Networks with Swift for Tensorflow Image Recognition and Dataset Categorization”?
ISBN-13: 9781484261675.
What are the book details (language, pages, edition)?
Language: en. Pages: 245. Edition: 1st ed..

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