Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML
Master the concepts of machine learning and build powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.
Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML
Nº de artículo: 19129724

Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML

Nº de artículo: 19129724

NIO 2323

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Master the concepts of machine learning and build powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.
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What Stands Out

Cross-Platform Development
Empowers developers to create robust mobile applications for both Android and iOS, ensuring a wider reach and usability in diverse mobile environments.
Advanced ML Integration
Utilizes TensorFlow Lite and Core ML to seamlessly integrate machine learning capabilities, enhancing app functionality and user experience through intelligent features.
Hands-On Projects
Offers practical, project-based learning experiences that enable users to apply machine learning concepts directly in real-world mobile applications, boosting skills and market readiness.

Detalles de producto

Shop Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML online at a best price in Nicaragua. 1788994590
  • Explore machine learning concepts for mobile applications
  • Build Android and iOS apps using TensorFlow Lite and Core ML
  • Learn age and gender detection using TensorFlow Lite and Core ML
  • Implement neural style transfer on photos
  • Work with ML Kit for Firebase for in-text detection, face detection, and barcode scanning
  • Create a Snapchat-like AR filter using OpenCV
Publisher Packt Publishing
Publication date October 31, 2018
Language English
Print length 246 pages
ISBN-10 1788994590
ISBN-13 978-1788994590
Item Weight 1.06 pounds (480 grams)
Dimensions 7.5 x 0.56 x 9.25 inches (19.1 x 1.4 x 23.5 cm)

Who Should Buy?

Suitable For
  • Mobile Developers

    Developers looking to integrate machine learning into their Android or iOS applications using TensorFlow Lite and Core ML.

  • Data Scientists

    Data scientists wanting to gain practical experience in deploying machine learning models on mobile platforms.

  • Students Learning ML

    Students seeking to learn about mobile applications with real-world machine learning projects and practical implementations.

Not Suitable For
  • Beginner Programmers

    Complete beginners may struggle with the concepts and coding required for implementing machine learning in mobile apps.

  • Non-Technical Users

    Individuals without a programming background will find the technical content challenging and difficult to comprehend.

  • General Audience

    Casual readers or users seeking basic information on machine learning without the need for coding or advanced applications.

DESCRIPCIÓN DEL PRODUCTO

About This Item

Introducing Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML Are you ready to take your mobile app development skills to the next level? With Machine Learning Projects for Mobile Applications, you can now learn how to build Android and iOS applications using cutting-edge machine learning technologies like TensorFlow Lite and Core ML. Whether you're a beginner or an experienced mobile developer, this comprehensive guide is packed with step-by-step tutorials, real-world examples, and hands-on projects that will help you harness the power of machine learning in your Android and iOS apps. With the rise of artificial intelligence and machine learning, integrating intelligent features into mobile applications has become a must for developers. By leveraging TensorFlow Lite, an open-source machine learning framework for mobile devices, and Core ML, a machine learning framework specifically designed for Apple devices, you'll be able to create intelligent and dynamic mobile apps that can analyze data, recognize objects, and make predictions in real-time. This book covers a wide range of topics, including Android machine learning projects, iOS machine learning projects, mobile app development with machine learning, TensorFlow Lite for mobile applications, Core ML for mobile applications, and much more.

You'll learn how to train machine learning models, integrate them into your apps, and optimize their performance for mobile devices. Discover how to build intelligent image recognition apps, automate tedious tasks using natural language processing, create predictive models for forecasting and recommendation systems, and much more. With the guidance of this book, you'll have the necessary skills and knowledge to develop advanced machine learning-powered mobile applications that will delight your users and set your apps apart from the competition. Unleash the potential of machine learning in mobile app development. Get your copy of Machine Learning Projects for Mobile Applications today and start building intelligent Android and iOS apps using TensorFlow Lite and Core ML.

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Preguntas y respuestas de los clientes

  • Pregunta: What are the key tasks that can be accomplished using this book?

    Respuesta: This book introduces readers to the basics of machine learning concepts for mobile applications and delves into real-world tasks such as detecting handwritten text, creating custom filters, and classifying food.
  • Pregunta: What programming languages are required to understand the book?

    Respuesta: Basic knowledge of Python programming language would be an added advantage.
  • Pregunta: What sets this book apart from other machine learning books?

    Respuesta: Readers will learn how to build apps for Android and iOS using Caffe, Core ML, and Tensorflow Lite and will be able to master the concepts of machine learning and build powerful apps on mobiles.

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ventajas

  • Innovative project ideas
  • User-friendly approach
  • Real-world applications
  • Great for beginners
  • Well-structured content

Contras

  • May need basic coding knowledge

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