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02489nam a2200445 4500 |
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978-1-4842-4297-1 |
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190220s2019 xxu| s |||| 0|eng d |
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|a 9781484242971
|9 978-1-4842-4297-1
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|a 10.1007/978-1-4842-4297-1
|2 doi
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|a 004.165
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|a Thakkar, Mohit.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Beginning Machine Learning in iOS
|h [electronic resource] :
|b CoreML Framework /
|c by Mohit Thakkar.
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|a 1st ed. 2019.
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|a Berkeley, CA :
|b Apress :
|b Imprint: Apress,
|c 2019.
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|a XI, 157 p. 112 illus.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
|2 rda
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|a 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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|a 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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|a Apple computer.
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|a Apple and iOS.
|0 http://scigraph.springernature.com/things/product-market-codes/I29020
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9781484242964
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|i Printed edition:
|z 9781484242988
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|u https://doi.org/10.1007/978-1-4842-4297-1
|z Full Text via HEAL-Link
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|a ZDB-2-CWD
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|a Professional and Applied Computing (Springer-12059)
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