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Machine Learning with Swift

You're reading from Machine Learning with Swift Artificial Intelligence for iOS

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781787121515

Length 378 pages

Edition 1st Edition

Languages

Swift

Tools

iOS

Concepts

Artificial Intelligence

Authors (3):

Jojo Moolayil

Oleksandr Baiev

Alexander Sosnovshchenko

View More author details

Table of Contents (14) Chapters

Preface

1. Getting Started with Machine Learning FREE CHAPTER

2. Classification – Decision Tree Learning

3. K-Nearest Neighbors Classifier

4. K-Means Clustering

5. Association Rule Learning

6. Linear Regression and Gradient Descent

7. Linear Classifier and Logistic Regression

8. Neural Networks

9. Convolutional Neural Networks

10. Natural Language Processing

11. Machine Learning Libraries

12. Optimizing Neural Networks for Mobile Devices

13. Best Practices

Introducing computer vision problems

In this book, we mentioned computer vision several times, but since this chapter is focused on this particular domain, we will look at it in more detail now. There are several practical tasks related to image and video processing, which are referred to as computer vision domain. While working on some computer vision task, it's important to know these names, to be able to find what you need in the vast ocean of computer vision publications:

Object recognition: The same as classification. Assigning labels to the images. This is a cat. Age estimation. Facial expression recognition.
Object localization: Finding frame of object in the image. The cat is in this frame.
Object detection: Finding frames of objects in the image. The cat is in this frame.
Semantic segmentation: Each point in the picture is assigned to one class. If the picture contains several cats, each cat's pixel would be assigned to the cat class.
Instance segmentation: Each point in the picture...

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Authors (3)

Alexander Sosnovshchenko

Alexander Sosnovshchenko

Alexander Sosnovshchenko has been working as an iOS software engineer since 2012. Later he made his foray into data science, from the first experiments with mobile machine learning in 2014, to complex deep learning solutions for detecting anomalies in video surveillance data. He lives in Lviv, Ukraine, and has a wife and a daughter.

See other products by Alexander Sosnovshchenko

Jojo Moolayil

Jojo Moolayil

Jojo Moolayil is an artiﬁcial intelligence, deep learning, machine learning, and decision science professional with over six years of industrial experience. He is the author of Learn Keras for Deep Neural Networks, published by Apress, and Smarter Decisions – The Intersection of IoT and Decision Science, published by Packt Publishing. He has worked with several industry leaders on high-impact, critical data science and machine learning projects across multiple verticals. He is currently associated with Amazon Web Services as a research scientist in Canada. Apart from writing books on AI, decision science, and the internet of things, Jojo has been a technical reviewer for various books in the same ﬁelds published by Apress and Packt Publishing.

See other products by Jojo Moolayil

Oleksandr Baiev

Oleksandr Baiev

See other products by Oleksandr Baiev

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