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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.
What You´ll Learn

Understand the CoreML components

Train custom models

Implement GPU processing for better computation efficiency

Enable machine learning in your application
Who This Book Is For

Novice developers and programmers who wish to implement machine learning in their iOS applications and those who want to learn the fundamentals about machine learning.

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Beginning Machine Learning in iOS
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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Mohit Thakkar is an Associate Software Engineer with MNC. He has a bachelor´s degree in computer engineering and is the author of several independently published titles, including Artificial Intelligence, Data Mining & Business Intelligence, iOS Programming, and Mobile Computing & Wireless Communication. He also published a research paper titled "Remote Health Monitoring using Implantable Probes to Prevent Untimely Death of Animals" in the International Journal of Advanced Research in Management, Architecture, Technology and Engineering.

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