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.

在学习Tensorflow和深度学习的同时，深入研究并应用实用的机器学习和数据集分类技术。本书使用卷积神经网络来进行图像识别，所有这些都是在熟悉和容易操作的Swift语言中进行的。

本书从基本的机器学习概述开始，然后逐步提升到神经网络和卷积以及它们的工作原理。使用Swift和Tensorflow，你将执行数据增强，建立和训练大型网络，并为移动设备建立网络。你还会涉及云训练，你构建的网络可以对灰度数据进行分类，如mnist，到可以对大型数据集进行分类的大规模现代方法，如imagenet。 

Tensorflow的Swift卷积神经网络使用一种简单的方法，逐步增加复杂度，直到你达到这一领域的技术现状。

你将会学到什么

- 对数据集进行分类和扩充

- 构建和训练大型网络，包括通过云解决方案

- 将复杂的系统部署到移动设备上

本书适用对象

有Swift编程经验的开发者，希望以Swift for Tensorflow为起点，通过实例学习卷积神经网络。