Ai And Machine Learning For On Device Development


Ai And Machine Learning For On Device Development
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Ai And Machine Learning For On Device Development


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.


Chapter 2. Introduction to Computer Vision -- Using Neurons for Vision -- Your First Classifier: Recognizing Clothing Items -- The Data: Fashion MNIST -- A Model Architecture to Parse Fashion MNIST -- Coding the Fashion MNIST Model -- Transfer Learning for Computer Vision -- Summary -- Chapter 3. Introduction to ML Kit -- Building a Face Detection App on Android -- Step 1: Create the App with Android Studio -- Step 2: Add and Configure ML Kit -- Step 3: Define the User Interface -- Step 4: Add the Images as Assets -- Step 5: Load the UI with a Default Picture.



Ai And Machine Learning For On Device Development


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 And Machine Learning For Coders


Ai And Machine Learning For Coders
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Author : Laurence Moroney
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-01

Ai And Machine Learning For Coders 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 2020-10-01 with Computers categories.


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 How to serve models over the web and in the cloud with TensorFlow Serving



Mobile Artificial Intelligence Projects


Mobile Artificial Intelligence Projects
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Author : Karthikeyan NG
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-30

Mobile Artificial Intelligence Projects 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 2019-03-30 with Computers categories.


Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key FeaturesBuild practical, real-world AI projects on Android and iOSImplement tasks such as recognizing handwritten digits, sentiment analysis, and moreExplore the core functions of machine learning, deep learning, and mobile visionBook Description We’re witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learnExplore the concepts and fundamentals of AI, deep learning, and neural networksImplement use cases for machine vision and natural language processingBuild an ML model to predict car damage using TensorFlowDeploy TensorFlow on mobile to convert speech to textImplement GAN to recognize hand-written digitsDevelop end-to-end mobile applications that use AI principlesWork with popular libraries, such as TensorFlow Lite, CoreML, and PyTorchWho this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.



Practical Deep Learning For Cloud Mobile And Edge


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



Tinyml Cookbook


Tinyml Cookbook
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Author : Gian Marco Iodice
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-01

Tinyml Cookbook written by Gian Marco Iodice 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 2022-04-01 with Computers categories.


Work through over 50 recipes to develop smart applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico using the power of machine learning Key Features Train and deploy ML models on Arduino Nano 33 BLE Sense and Raspberry Pi Pico Work with different ML frameworks such as TensorFlow Lite for Microcontrollers and Edge Impulse Explore cutting-edge technologies such as microTVM and Arm Ethos-U55 microNPU Book DescriptionThis book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.What you will learn Understand the relevant microcontroller programming fundamentals Work with real-world sensors such as the microphone, camera, and accelerometer Run on-device machine learning with TensorFlow Lite for Microcontrollers Implement an app that responds to human voice with Edge Impulse Leverage transfer learning to classify indoor rooms with Arduino Nano 33 BLE Sense Create a gesture-recognition app with Raspberry Pi Pico Design a CIFAR-10 model for memory-constrained microcontrollers Run an image classifier on a virtual Arm Ethos-U55 microNPU with microTVM Who this book is for This book is for machine learning developers/engineers interested in developing machine learning applications on microcontrollers through practical examples quickly. Basic familiarity with C/C++, the Python programming language, and the command-line interface (CLI) is required. However, no prior knowledge of microcontrollers is necessary.



Hands On Artificial Intelligence For Android


Hands On Artificial Intelligence For Android
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Author : Vasco Correia Veloso
language : en
Publisher: BPB Publications
Release Date : 2022-01-27

Hands On Artificial Intelligence For Android written by Vasco Correia Veloso and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-27 with Computers categories.


Build machine learning models and train them to make Android applications much smarter. KEY FEATURES ● Learn by doing, training, and evaluating your own machine learning models. ● Includes pre-trained TensorFlow models for image processing. ● Explains practical use cases of artificial intelligence in Android. DESCRIPTION This book features techniques and real implementations of machine learning applications on Android phones. This book covers various developer tools, including TensorFlow and Google ML Kit. The book begins with a quick review of android application development fundamentals and a couple of Java and Kotlin implementations developed using the Android Studio integrated development environment. The book explores TensorFlow Lite and Google ML Kit, along with some of the most widely used machine learning techniques. The book covers real projects on TensorFlow, demonstrates how to collect photos with Camera X, and preprocess them with the Google ML Kit. It explains how to onboard the power of machine learning in Android applications that detect images, identify faces, and apply effects to photographs, among other things. These applications are constructed on top of TensorFlow models – some of which were created and trained by the reader – and then converted to TensorFlow Lite for mobile applications. After reading the book, the reader will be able to apply machine learning techniques to create Android applications and take their applications to the next level. This book can be a successful tool to deep dive into Data Science for all mobile programmers. WHAT YOU WILL LEARN ● Get well-versed with Android Development and the fundamentals of AI. ● Learn to set up the ML environment with hands-on knowledge of TensorFlow. ● Build, train, and evaluate Machine Learning models. ● Practice ML by working on real face verification and identification applications. ● Explore cutting-edge models such as GAN and RNN in detail. ● Experience the use of CameraX, SQLite, and Google ML Kit on Android. WHO THIS BOOK IS FOR This book is intended for android developers, application engineers, machine learning engineers, and anybody interested in infusing intelligent, inventive, and smart features into mobile phones. Readers should have a basic understanding of the Java programming language. TABLE OF CONTENTS 1. Building an Application with Android Studio and Java 2. Event Handling and Intents in Android 3. Building our Base Application with Kotlin and SQLite 4. An Overview of Artificial Intelligence and Machine Learning 5. Introduction to TensorFlow 6. Training a Model for Image Recognition with TensorFlow 7. Android Camera Image Capture with CameraX 8. Using the Image Recognition Model in an Android Application 9. Detecting Faces with the Google ML Kit 10. Verifying Faces in Android with TensorFlow Lite 11. Registering Faces in the Application 12. Image Processing with Generative Adversarial Networks 13. Describing Images with NLP



Practical Ai On The Google Cloud Platform


Practical Ai On The Google Cloud Platform
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Author : Micheal Lanham
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-20

Practical Ai On The Google Cloud Platform written by Micheal Lanham 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 2020-10-20 with Computers categories.


Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI and AutoML Tables Build a simple language processor using deep learning systems Perform image recognition using CNNs, transfer learning, and GANs Use Google's Dialogflow to create chatbots and conversational AI Analyze video with automatic video indexing, face detection, and TensorFlow Hub Build a complete working AI agent application



Ai At The Edge


Ai At The Edge
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Author : Daniel Situnayake
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-01-10

Ai At The Edge written by Daniel Situnayake 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 2023-01-10 with Computers categories.


Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target--from ultra-low power microcontrollers to embedded Linux devices. This practical guide gives engineering professionals, including product managers and technology leaders, an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You'll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers. This high-level road map helps you get started. Develop your expertise in AI and ML for edge devices Understand which projects are best solved with edge AI Explore key design patterns for edge AI apps Learn an iterative workflow for developing AI systems Build a team with the skills to solve real-world problems Follow a responsible AI process to create effective products



Artificial Intelligence By Example


Artificial Intelligence By Example
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Author : Denis Rothman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31

Artificial Intelligence By Example written by Denis Rothman 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 2018-05-31 with Computers categories.


Be an adaptive thinker that leads the way to Artificial Intelligence Key Features AI-based examples to guide you in designing and implementing machine intelligence Develop your own method for future AI solutions Acquire advanced AI, machine learning, and deep learning design skills Book Description Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. What you will learn Use adaptive thinking to solve real-life AI case studies Rise beyond being a modern-day factory code worker Acquire advanced AI, machine learning, and deep learning designing skills Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology Understand future AI solutions and adapt quickly to them Develop out-of-the-box thinking to face any challenge the market presents Who this book is for Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book.