Machine Learning For Android App Development Using Ml Kit

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Machine Learning For Android App Development Using Ml Kit

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Author : Yusuf Saber
language : en
Publisher:
Release Date : 2018

Machine Learning For Android App Development Using Ml Kit written by Yusuf Saber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

"It's crazy to see how Artificial Intelligence and Machine Learning are moving so fast and becoming the next big thing. The focus is on putting AI and Machine Learning into people's hands in their daily lives by bringing it to their mobile devices. ML Kit makes it easy to apply ML techniques to your apps by bringing Google's ML technologies together in a single SDK. With ML Kit you can have features such as text recognition, face recognition, barcode scanning, image labeling, and landmark recognition at your fingertips in your apps. In this course, you are going to implement all these features in your Android applications using ML Kit. After completing this course, you will be confident enough to build Android applications equipped with in-built Machine Learning features, providing an amazing user experience. You will be able to go into the world and create your own useful Machine Learning apps using ML Kit."--Resource description page.

Ai And Machine Learning For On Device Development

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Author : Laurence Moroney
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-08-12

Ai And Machine Learning For On Device Development written by Laurence Moroney and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-12 with Computers categories.

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

Google Firebase Android Developer Certification

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Author :
language : en
Publisher: YouGuide Ltd
Release Date : 2024-10-26

Google Firebase Android Developer Certification written by and has been published by YouGuide Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with categories.

Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Mobile Deep Learning With Tensorflow Lite Ml Kit And Flutter

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Author : Anubhav Singh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-06

Mobile Deep Learning With Tensorflow Lite Ml Kit And Flutter written by Anubhav Singh and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-06 with Computers categories.

Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and Flutter Key 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 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 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 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.

Practical Deep Learning For Cloud Mobile And Edge

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Author : Anirudh Koul
language : en
Publisher: O'Reilly Media
Release Date : 2019-10-14

Practical Deep Learning For Cloud Mobile And Edge written by Anirudh Koul and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.

Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Kotlin Mastery

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Author : Arnika Patel
language : en
Publisher: Springer Nature
Release Date : 2025-09-30

Kotlin Mastery written by Arnika Patel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.

Enhance your programming toolkit and build robust applications by mastering Kotlin. This book connects Java and Kotlin through side-by-side code samples and practical demonstrations. Java programmers and up-and-coming developers seeking to learn Kotlin need to do so with confidence. Starting with the fundamentals of basic syntax, this book will cover data types, variables, control flow statements. From there move on to advanced topics like object-oriented programming concepts with null safety, lambdas, functions, inheritance and coroutines. Additionally, you’ll delve into practical applications such as designing custom domain-specific languages, working with Kotlin Multiplatform, and leveraging reactive extensions. With numerous hands-on exercises and real-world examples, you'll gain the expertise needed to explore advanced projects. What You Will Learn Explore object-oriented and functional programming with Kotlin to create modular code. Review Kotlin’s techniques for error handling and exception management. Implement Kotlin coroutines for efficient concurrency and asynchronous task management. Design custom domain-specific languages and use the Kotlin standard library for string manipulation and file handling. Who This Book is For: Java developers and programmers looking to master Kotlin.

Machine Learning Projects For Mobile Applications

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Author : Karthikeyan NG
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31

Machine Learning Projects For Mobile Applications written by Karthikeyan NG and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.

Bring magic to your mobile apps using TensorFlow Lite and Core ML Key FeaturesExplore machine learning using classification, analytics, and detection tasks.Work with image, text and video datasets to delve into real-world tasksBuild apps for Android and iOS using Caffe, Core ML and Tensorflow LiteBook Description Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google’s ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this book, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML. What you will learnDemystify the machine learning landscape on mobileAge and gender detection using TensorFlow Lite and Core MLUse ML Kit for Firebase for in-text detection, face detection, and barcode scanningCreate a digit classifier using adversarial learningBuild a cross-platform application with face filters using OpenCVClassify food using deep CNNs and TensorFlow Lite on iOS Who this book is for Machine Learning Projects for Mobile Applications is for you if you are a data scientist, machine learning expert, deep learning, or AI enthusiast who fancies mastering machine learning and deep learning implementation with practical examples using TensorFlow Lite and CoreML. Basic knowledge of Python programming language would be an added advantage.

Ai And Machine Learning On Device Development

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Author : Laurence Moroney
language : en
Publisher:
Release Date : 2021

Ai And Machine Learning On Device Development written by Laurence Moroney and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

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 models and running them 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--and when to use each 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 Understand how to choose the best techniques and tools for your use case: on-device inference versus cloud-based inference, high-level APIs versus low-level APIs, and more Learn privacy and ethics best practices for ML on devices.

Ai And Machine Learning For On Device Development

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Author : Laurence Moroney
language : en
Publisher: O'Reilly Media
Release Date : 2022-01-18

Ai And Machine Learning For On Device Development written by Laurence Moroney and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-18 with Computers categories.

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 models and running them 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--and when to use each 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 Understand how to choose the best techniques and tools for your use case: on-device inference versus cloud-based inference, high-level APIs versus low-level APIs, and more Learn privacy and ethics best practices for ML on devices

Ai Powered Mobile Apps With Kotlin And Android

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Author : Ralf Kohl
language : en
Publisher: Independently Published
Release Date : 2025-12-02

Ai Powered Mobile Apps With Kotlin And Android written by Ralf Kohl and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-02 with Computers categories.

AI-Powered Mobile Apps with Kotlin and Android Build Practical Image, Text, and Voice Features Using TensorFlow Lite, ML Kit, and Cloud AI What if your Android apps could analyze images instantly, understand user speech, process text intelligently, and adapt to each user, all while running smoothly on real devices? As AI becomes a standard expectation in mobile experiences, developers face a major challenge: delivering intelligent features that remain fast, private, and reliable across a wide range of hardware. AI-Powered Mobile Apps with Kotlin and Android provides a clear, production-focused path forward. This book shows you how to combine TensorFlow Lite, ML Kit, and cloud AI models to build features that balance accuracy, speed, and user trust. You learn practical methods used in professional Android development to integrate on-device machine learning, call cloud-based text intelligence only when necessary, and design app flows that behave consistently even when AI returns uncertain results. Every chapter centers on real implementation: image classification, OCR, text assistance, voice-driven features, and personalization. Clear Kotlin examples, step-by-step explanations, and real-device guidance help you translate theory into usable, maintainable applications. By reading this book, you will learn how to: - Build image classification and vision features using TensorFlow Lite - Implement fast OCR, barcode scanning, and translation using ML Kit - Add cloud-powered text generation and summarization with safe request handling - Create natural voice input and voice output flows using Android speech APIs - Apply personalization strategies using local user data and lightweight on-device models - Improve runtime performance with quantization, delegates, and latency testing - Deploy and update models safely through Play Asset Delivery and Remote Config - Design AI-friendly UI patterns that communicate confidence, handle edge cases, and protect user privacy If you want to create mobile apps that feel intelligent, responsive, and polished, without depending entirely on remote servers, this book gives you the roadmap and the working patterns to achieve it. Start building next-generation Android apps powered by practical, production-ready AI.