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Beginning machine learning in iOSCor...
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SpringerLink (Online service)
Beginning machine learning in iOSCoreML framework /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Beginning machine learning in iOSby Mohit Thakkar.
Reminder of title:
CoreML framework /
Author:
Thakkar, Mohit.
Published:
Berkeley, CA :Apress :2019.
Description:
xi, 157 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Machine learning.
Online resource:
https://doi.org/10.1007/978-1-4842-4297-1
ISBN:
9781484242971$q(electronic bk.)
Beginning machine learning in iOSCoreML framework /
Thakkar, Mohit.
Beginning machine learning in iOS
CoreML framework /[electronic resource] :by Mohit Thakkar. - Berkeley, CA :Apress :2019. - xi, 157 p. :ill., digital ;24 cm.
Chapter 1. Introduction to Machine Learning -- Chapter 2. Introduction to Core ML Framework -- Chapter 3. Custom ML Models Using Turi Create -- Chapter 4. Custom Core ML Models using Create ML -- Chapter 5. Improving Computational Efficiency.
Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to suggest which people that might be in a photo. You'll review how these types of machine learning tasks are implemented and performed so that you can use them in your own apps. Beginning Machine Learning in iOS is your guide to putting machine learning to work in your iOS applications.
ISBN: 9781484242971$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-4297-1doiSubjects--Uniform Titles:
iOS (Electronic resource)
Subjects--Topical Terms:
188639
Machine learning.
LC Class. No.: Q325.5
Dewey Class. No.: 006.31
Beginning machine learning in iOSCoreML framework /
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Chapter 1. Introduction to Machine Learning -- Chapter 2. Introduction to Core ML Framework -- Chapter 3. Custom ML Models Using Turi Create -- Chapter 4. Custom Core ML Models using Create ML -- Chapter 5. Improving Computational Efficiency.
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Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to suggest which people that might be in a photo. You'll review how these types of machine learning tasks are implemented and performed so that you can use them in your own apps. Beginning Machine Learning in iOS is your guide to putting machine learning to work in your iOS applications.
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Professional and Applied Computing (Springer-12059)
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