Machine Learning for iOS Developers PDF

Machine Learning for iOS Developers PDF

Name:
Machine Learning for iOS Developers PDF

Published Date:
02/01/2020

Status:
Active

Description:

Publisher:
John Wiley and Sons

Document status:
Active

Format:
Electronic (PDF)

Delivery time:
10 minutes

Delivery time (for Russian version):
200 business days

SKU:

Choose Document Language:
Need Help?

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 learning (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 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 & Keras models with CoreML

Machine Learning for iOS Developers is a must-have resource for software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS apps.


ISBN(s) : 9781119602903
Published : 02/01/2020

History


Related products


Best-Selling Products

BS ISO/IEC 10021-1:1990
Published Date: 03/29/1991
Information technology. Text communication. Message-oriented text interchange systems (MOTIS). System and service overview
$119.634
BS ISO/IEC 10021-2:1990
Published Date: 03/29/1991
Information technology. Message handling systems (MHS)-Information technology. Text communication. Message-oriented text interchange systems (MOTIS). Overall architecture
$119.634
BS ISO/IEC 10021-2:1996
Published Date: 01/15/1998
Information technology. Message handling systems (MHS)-Overall architecture
$119.634
BS ISO/IEC 10021-3:1990
Published Date: 03/29/1991
Information technology. Text communication. Message-oriented text interchange systems (MOTIS). Abstract service definition conventions
$92.964
BS ISO/IEC 10021-4:1990
Published Date: 03/29/1991
Information technology. Text communication. Message-oriented text interchange systems (MOTIS). Message transfer system: abstract service definition and procedures
$119.634
BS ISO/IEC 10021-4:1997
Published Date: 01/15/1998
Information technology. Message handling systems (MHS)-Message transfer system. Abstract service definition and procedures
$119.634