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Beginning Machine Learning in iOS : CoreML Framework / by Mohit Thakkar

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink Bücher | Springer eBook CollectionPublisher: [Berkeley, CA] : Apress, [2019]Copyright date: © 2019Description: 1 Online-Ressource (XI, 157 Seiten) : 112 IllustrationenISBN:
  • 9781484242971
Subject(s): Additional physical formats: 9781484242964 | 9781484242988 | Erscheint auch als: 978-1-4842-4296-4 Druck-AusgabeDDC classification:
  • 004.165
LOC classification:
  • QA76.8.M3 QA76.774.I67
  • QA76.8.M3
  • QA76.774.I67
DOI: DOI: 10.1007/978-1-4842-4297-1Online resources: Summary: 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 applicationsSummary: 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 EfficiencyPPN: PPN: 106737311XPackage identifier: Produktsigel: ZDB-2-CWD | ZDB-2-SEB | ZDB-2-SXPC
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Reproduktion. (Springer eBook Collection. Professional and Applied Computing)

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