Convolutional Neural Networks with Swift for Tensorflow

Image Recognition and Dataset Categorization
1. Auflage 2021
ISBN: 978-1-4842-6167-5
Verlag: Apress

Buch, Englisch, 245 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 411 g

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Koonce, Brett

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Macintosh Programmierung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Betriebssysteme Mac OS, Mac OS X

Inhaltsverzeichnis

Chapter 1: MNIST: 1D Neural Network.- Chapter 2: MNIST: 2D Neural Network.- Chapter 3: CIFAR: 2D Nueral Network with Blocks.- Chapter 4: VGG Network.- Chapter 5: Resnet 34.- Chapter 6: Resnet 50.- Chapter 7: SqueezeNet.- Chapter 8: MobileNrt v1.- Chapter 9: MobileNet v2.- Chapter 10: Evolutionary Strategies.- Chapter 11: MobileNet v3.- Chapter 12: Bag of Tricks.- Chapter 13: MNIST Revisited.- Chapter 14: You are Here.

Über Autor(innen)

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.