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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter (eBook)

Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
eBook Download: EPUB
2020
380 Seiten
Packt Publishing (Verlag)
978-1-78961-399-5 (ISBN)

Lese- und Medienproben

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter - Anubhav Singh, Rimjhim Bhadani
35,41 € (CHF 34,60)
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36,59 € (CHF 35,75)
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Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and Flutter




Key Features



  • Work through projects covering mobile vision, style transfer, speech processing, and multimedia processing


  • Cover interesting deep learning solutions for mobile


  • Build your confidence in training models, performance tuning, memory optimization, and neural network deployment through every project



Book Description



Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more.







With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You'll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.







By the end of this book, you'll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.




What you will learn



  • Create your own customized chatbot by extending the functionality of Google Assistant


  • Improve learning accuracy with the help of features available on mobile devices


  • Perform visual recognition tasks using image processing


  • Use augmented reality to generate captions for a camera feed


  • Authenticate users and create a mechanism to identify rare and suspicious user interactions


  • Develop a chess engine based on deep reinforcement learning


  • Explore the concepts and methods involved in rolling out production-ready deep learning iOS and Android applications



Who this book is for



This book is for data scientists, deep learning and computer vision engineers, and natural language processing (NLP) engineers who want to build smart mobile apps using deep learning methods. You will also find this book useful if you want to improve your mobile app's user interface (UI) by harnessing the potential of deep learning. Basic knowledge of neural networks and coding experience in Python will be beneficial to get started with this book.


Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and FlutterKey FeaturesWork through projects covering mobile vision, style transfer, speech processing, and multimedia processingCover interesting deep learning solutions for mobileBuild your confidence in training models, performance tuning, memory optimization, and neural network deployment through every projectBook DescriptionDeep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more.With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You'll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.By the end of this book, you'll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.What you will learnCreate your own customized chatbot by extending the functionality of Google AssistantImprove learning accuracy with the help of features available on mobile devicesPerform visual recognition tasks using image processingUse augmented reality to generate captions for a camera feedAuthenticate users and create a mechanism to identify rare and suspicious user interactionsDevelop a chess engine based on deep reinforcement learningExplore the concepts and methods involved in rolling out production-ready deep learning iOS and Android applicationsWho this book is forThis book is for data scientists, deep learning and computer vision engineers, and natural language processing (NLP) engineers who want to build smart mobile apps using deep learning methods. You will also find this book useful if you want to improve your mobile app's user interface (UI) by harnessing the potential of deep learning. Basic knowledge of neural networks and coding experience in Python will be beneficial to get started with this book.
Erscheint lt. Verlag 6.4.2020
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Netzwerke
Informatik Software Entwicklung Mobile- / App-Entwicklung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Deep learning • machine learning • mobile deep learning • Neural networks • TensorFlow Lite
ISBN-10 1-78961-399-X / 178961399X
ISBN-13 978-1-78961-399-5 / 9781789613995
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Dateiformat: EPUB (Electronic Publication)
EPUB ist ein offener Standard für eBooks und eignet sich besonders zur Darstellung von Belle­tristik und Sach­büchern. Der Fließ­text wird dynamisch an die Display- und Schrift­größe ange­passt. Auch für mobile Lese­geräte ist EPUB daher gut geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür die kostenlose Software Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür eine kostenlose App.
Geräteliste und zusätzliche Hinweise

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

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