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 Applesquo;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 analytics
Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming
Develop 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 lKeras 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.
