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.
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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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.
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.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 LearnUnderstand the CoreML componentsTrain custom modelsImplement GPU processing for better computation efficiencyEnable machine learning in your applicationWho This Book Is ForNovice developers and programmers who wish to implement machine learning in their iOS applications and those who want to learn the fundamentals about machine learning. 172 pp. Englisch. Nº de ref. del artículo: 9781484242964
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 LearnUnderstand the CoreML componentsTrain custom modelsImplement GPU processing for better computation efficiencyEnable machine learning in your applicationWho This Book Is ForNovice developers and programmers who wish to implement machine learning in their iOS applications and those who want to learn the fundamentals about machine learning. Nº de ref. del artículo: 9781484242964
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 subjectTeaches the concepts important specifically to CoreML and how. Nº de ref. del artículo: 251556709
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