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  • 1
    Orig.schr. Ausgabe: 初版.
    Title: 動かして学ぶAI・機械学習の基礎 : : TensorFlowによるコンピュータビジョン, 自然言語処理, 時系列データの予測とデプロイ /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873119809 , 4873119804
    Language: Japanese
    Pages: 1 online resource (384 pages)
    Edition: Shohan.
    Uniform Title: AI and machine learning for coders
    DDC: 006.3/1
    Keywords: Machine learning ; Artificial intelligence
    Note: In Japanese.
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  • 2
    ISBN: 9788328378513 , 8328378515
    Language: Polish
    Pages: 1 online resource (352 pages) , illustrations
    Edition: [First edition].
    Uniform Title: AI and machine learning for coders
    DDC: 006.3/1
    Keywords: Machine learning ; Artificial intelligence
    Abstract: Sztuczna inteligencja i uczenie maszynowe znajdują coraz więcej zastosowań w niemal wszystkich istotnych branżach. W technologiach sieci neuronowych tkwi olbrzymi potencjał. Za rozwojem uczenia maszynowego muszą nadążać architekci i programiści: aplikacja, w której wykorzystano technologie sztucznej inteligencji, musi pasować do określonego zastosowania. Poszczególne systemy różnią się od siebie, tak samo jak różne są rozwiązywane przez nie problemy. Sztuczna inteligencja ujawni swoje ogromne możliwości tylko, jeśli inżynierowie dostosują swoje aplikacje do rozwiązywania konkretnych problemów. Ta książka jest praktycznym podręcznikiem opartym na sprawdzonej metodyce: nauce poprzez pisanie kodu w Pythonie. Aby w pełni z niego skorzystać, nie musisz znać wyższej matematyki. Dzięki praktycznym lekcjom szybko zaczniesz programowo tworzyć konkretne rozwiązania. Dowiesz się, jak można zaimplementować najważniejsze algorytmy uczenia maszynowego, korzystając ze znakomitej biblioteki TensorFlow. Nauczysz się też, w jaki sposób wdrażać modele uczenia maszynowego i tworzyć przydatne aplikacje, które będą działały w różnych środowiskach i na różnych platformach: przykładowo napiszesz aplikację w języku Kotlin w środowisku Android Studio czy też w języku Swift w środowisku Xcode.
    Note: Includes index
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  • 3
    Online Resource
    Online Resource
    [Place of publication not identified] : Ascent Audio
    ISBN: 9781663720979 , 1663720975
    Language: English
    Pages: 1 online resource (1 audio file (9 hr., 17 min.))
    Edition: [First edition].
    DDC: 006.31
    Keywords: Application software Development ; Machine learning ; Mobile computing ; Audiobooks ; Handbooks and manuals
    Abstract: AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android. Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today. - Explore the options for implementing ML and AI on mobile devices - Create ML models for iOS and Android - Write ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOS - Choose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIs - Learn privacy and ethics best practices for ML on devices.
    Note: Online resource; title from title details screen (O'Reilly, viewed December 13, 2022)
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  • 4
    ISBN: 9781663721372 , 1663721378
    Language: English
    Pages: 1 online resource (1 audio file (9 hr., 17 min.))
    Edition: [First edition].
    DDC: 006.31
    Keywords: Machine learning ; Artificial intelligence ; Audiobooks
    Abstract: If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: how to build models with TensorFlow using skills that employers desire; the basics of machine learning by working with code samples; how to implement computer vision, including feature detection in images; how to use NLP to tokenize and sequence words and sentences; methods for embedding models in Android and iOS; and how to serve models over the web and in the cloud with TensorFlow Serving.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 31, 2023)
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