Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner!
Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.
Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models―both pre-trained and user-built―with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:
Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
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Abhishek Mishra has more than 19 years of experience across a broad range of mobile and enterprise technologies. He consults as a security and fraud solution architect with Lloyds Banking group PLC in London. He is the author of Machine Learning on the AWS Cloud, Amazon Web Services for Mobile Developers, iOS Code Testing, and Swift iOS: 24-Hour Trainer.
Learn how to harness machine learning in your iOS apps!
Machine Learning (ML) is a discipline within Artificial Intelligence (AI) that enables computers to learn patterns from data and use these patterns to categorize and predict information reliably and quickly without being explicitly programmed. The Apple iOS Software Development Kit (SDK) includes the Core ML framework that allows developers to integrate ML services into both mobile and desktop applications. Assuming no prior experience in the field, Machine Learning for iOS Developers covers building machine learning models with Apple's new Create ML app, as well as building models using popular Python libraries such as NumPy, Pandas, Scikit-learn and Keras. The book then teaches you how to integrate these models in iOS applications using Apple's Core ML framework and the Core ML tools library. Step-by-step guidance, hands-on activities, real-world scenarios, and downloadable source code examples make Machine Learning for iOS Developers a must-have resource for anyone wishing to learn the concepts and techniques needed to be a successful Apple iOS Machine Learning practitioner.
This practical, clearly-written guide shows how to:
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Paperback. Zustand: New. Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models-both pre-trained and user-built-with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analyticsBuild, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streamingDevelop skills in data acquisition and modeling, classification, and regression.Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn and Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps. Bestandsnummer des Verkäufers LU-9781119602873
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Paperback. Zustand: New. Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models-both pre-trained and user-built-with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analyticsBuild, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streamingDevelop skills in data acquisition and modeling, classification, and regression.Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn and Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps. Bestandsnummer des Verkäufers LU-9781119602873
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