Convolutional Neural Networks with Swift for Tensorflow (PDF)

Name: Convolutional Neural Networks with Swift for Tensorflow
Brand: APress
SKU: 139133362
Price: 56.99 EUR
Availability: OnlineOnly

Image Recognition and Dataset Categorization (Sprache: Englisch)

Autor: Brett Koonce

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Convolutional Neural Networks with Swift for Tensorflow, Brett Koonce

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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....

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Produktinformationen zu „Convolutional Neural Networks with Swift for Tensorflow (PDF)“

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.

You will:

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

Autoren-Porträt von Brett Koonce

Brett Koonce is the CTO of Quarkworks, a mobile consulting agency. He's a developer with five years experience creating apps for iOS and Android. His team has worked on dozens of apps that are used by millions of people around the world. Brett knows the pitfalls of development and can help you avoid them. Whether you want to build something from scratch, port your app from iOS to Android (or vice versa) or accelerate your velocity, Brett can help.

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Autor: Brett Koonce
2021, 1st ed, 245 Seiten, Englisch
Verlag: APress
ISBN-10: 1484261682
ISBN-13: 9781484261682
Erscheinungsdatum: 04.01.2021

Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.

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Dateiformat: PDF
Größe: 2.13 MB
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Sprache:

Englisch

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