Machine Learning In Mobile Applications
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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.
Machine Learning For Mobile
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Author : Revathi Gopalakrishnan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31
Machine Learning For Mobile written by Revathi Gopalakrishnan 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 2018-12-31 with Computers categories.
Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease Key FeaturesBuild smart mobile applications for Android and iOS devicesUse popular machine learning toolkits such as Core ML and TensorFlow LiteExplore cloud services for machine learning that can be used in mobile appsBook Description Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices. What you will learnBuild intelligent machine learning models that run on Android and iOSUse machine learning toolkits such as Core ML, TensorFlow Lite, and moreLearn how to use Google Mobile Vision in your mobile appsBuild a spam message detection system using Linear SVMUsing Core ML to implement a regression model for iOS devicesBuild image classification systems using TensorFlow Lite and Core MLWho this book is for If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus
Designing And Developing Innovative Mobile Applications
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Author : Samanta, Debabrata
language : en
Publisher: IGI Global
Release Date : 2023-04-12
Designing And Developing Innovative Mobile Applications written by Samanta, Debabrata and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-12 with Technology & Engineering categories.
Since mobile communication has become so ingrained in our daily lives, many people find it difficult to function without a cellphone. When the phone first came out, the only commonly used features were calling and sending text messages (texts). The intelligent mobile phone has proven to be a multipurpose tool that works best for communication and aids in learning, earning, and having fun. This in turn prompted several developers to consider creating mobile applications. Designing and Developing Innovative Mobile Applications focuses on the fundamentals of the Android OS and its device features, the deployment of any Android application, and the activities and intents of Android programming. Covering key topics such as mobile pages, software development, and communication, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Machine Learning With Core Ml
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Author : Joshua Newnham
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-28
Machine Learning With Core Ml written by Joshua Newnham 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 2018-06-28 with Computers categories.
Leverage the power of Apple's Core ML to create smart iOS apps Key Features Explore the concepts of machine learning and Apple’s Core ML APIs Use Core ML to understand and transform images and videos Exploit the power of using CNN and RNN in iOS applications Book Description Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs What you will learn Understand components of an ML project using algorithms, problems, and data Master Core ML by obtaining and importing machine learning model, and generate classes Prepare data for machine learning model and interpret results for optimized solutions Create and optimize custom layers for unsupported layers Apply CoreML to image and video data using CNN Learn the qualities of RNN to recognize sketches, and augment drawing Use Core ML transfer learning to execute style transfer on images Who this book is for Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers.
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.
Machine Learning In Mobile Applications
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Author :
language : en
Publisher:
Release Date : 2019
Machine Learning In Mobile Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Learn how to apply the power of machine learning to mobile app development, using platforms such as IBM Watson, Microsoft Azure Cognitive Services, and Apple Core ML.
Online Social Networks In Business Frameworks
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Author : Sudhir Kumar Rathi
language : en
Publisher: John Wiley & Sons
Release Date : 2024-09-17
Online Social Networks In Business Frameworks written by Sudhir Kumar Rathi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Business & Economics categories.
This book presents a vital method for companies to connect with potential clients andconsumers in the digital era of Online Social Networks (OSNs), utilizing the strengthof well-known social networks and AI to achieve success through fostering brandsupporters, generating leads, and enhancing customer interactions. There are currently 4.8 billion Online Social Network (OSN) users worldwide. Online Social Networks in Business Frameworks presents marketing through online social networks (OSNs), which is a potent method for companies of all sizes to connect with potential clients and consumers. If visitors are not on OSN sites like Facebook, Twitter, and LinkedIn, they are missing out on the fact that people discover, learn about, follow, and purchase from companies on OSNs. Excellent OSN advertising may help a company achieve amazing success by fostering committed brand supporters and even generating leads and revenue. A type of digital advertising known as social media marketing (SMM) makes use of the strength of well-known social networks to further advertise and establish branding objectives. Nevertheless, it goes beyond simply setting up company accounts and tweeting whenever visitors feel like it. Preserving and improving profiles means posting content that represents the company and draws in the right audience, such as images, videos, articles, and live videos, addressing comments, shares, and likes while keeping an eye on the reputation to create a brand network, and following and interacting with followers, clients, and influencers.
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.
Security Incidents Response Against Cyber Attacks
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Author : Akashdeep Bhardwaj
language : en
Publisher: Springer Nature
Release Date : 2021-07-07
Security Incidents Response Against Cyber Attacks written by Akashdeep Bhardwaj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-07 with Technology & Engineering categories.
This book provides use case scenarios of machine learning, artificial intelligence, and real-time domains to supplement cyber security operations and proactively predict attacks and preempt cyber incidents. The authors discuss cybersecurity incident planning, starting from a draft response plan, to assigning responsibilities, to use of external experts, to equipping organization teams to address incidents, to preparing communication strategy and cyber insurance. They also discuss classifications and methods to detect cybersecurity incidents, how to organize the incident response team, how to conduct situational awareness, how to contain and eradicate incidents, and how to cleanup and recover. The book shares real-world experiences and knowledge from authors from academia and industry.
Computational Intelligence
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Author : T. Ananth Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-22
Computational Intelligence written by T. Ananth Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.
This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system’s physiological characteristics and has been implemented numerically for non-linear mapping. Fuzzy Logic Systems simulate the human brain’s psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into computational intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems.