rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Machine learning for ios developers
  name:
    name part: Mishra, Abhishek
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: handbook
  genre: elektronické knihy
  genre: příručky
  genre: electronic books
  genre: handbooks and manuals
  origin info:
    place:
      place term: xx
    date issued: 2020
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online zdroj
  abstract: 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 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 f…
  target audience: specialized
  note: Abhishek Mishra.
  note: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty univerzity
  subject:
    topic: strojové učení
  subject:
    topic: Apple iOS (operační systém)
  subject:
    topic: machine learning
  subject:
    topic: Apple iOS (operating system)
  classification: 004.85
  classification: 004.451.9iOS
  classification: (0.034.2:08)
  classification: (035)
  related item:
    title info:
      title: Machine learning for ios developers
    name:
      name part: Mishra, Abhishek.
    origin info:
      publisher: [Place of publication not identified] : John Wiley And Sons, Inc, 2020
    identifier: (OCoLC)1125970961
  identifier: 9781119602927
  identifier: 9781119602910
  identifier: 9781119602903
  identifier: 9781119602873
  identifier: https://proxy.k.utb.cz/login
  access condition: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty univerzity
  record info:
    record content source: YDX
    record creation date: 200220
    record change date: 20251008112130.0
    record identifier: 107960
    language of cataloging:
      language term: eng