Beginning Machine Learning in iOS

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.

  Introduces the general concepts of Machine Learning as well as how they specifically pertain to iOS Provides practical examples with illustrations that give more clarity on the subject Teaches the concepts important specifically to CoreML and how they have been implemented in popular apps

  Autorentext
  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.

  Inhalt
  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.