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Condizione: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

Paperback. Condizione: New. First Edition. This book offers both theoretical insights and hands-on experience in understanding and building machine learning-based Network Traffic Monitoring and Analysis (NTMA) and Video Quality Assessment (VQA) applications using JavaScript. JavaScript provides the flexibility to deploy these applications across various devices and web browsers. The book begins by delving into NTMA, explaining fundamental concepts and providing an overview of existing applications and research within this domain. It also goes into the essentials of VQA and offers a survey of the latest developments in VQA algorithms. The book includes a thorough examination of machine learning algorithms that find application in both NTMA and VQA, with a specific emphasis on classification and prediction algorithms such as the Multi-Layer Perceptron and Support Vector Machine. The book also explores the software architecture of the NTMA client-server application. This architecture is meticulously developed using HTML, CSS, Node.js, and JavaScript. Practical aspects of developing the Video Quality Assessment (VQA) model using JavaScript and Java are presented. Lastly, the book provides detailed guidance on implementing a complete system model that seamlessly merges NTMA and VQA into a unified web application, all built upon a client-server paradigm. By the end of the book, you will understand NTMA and VQA concepts and will be able to apply machine learning to both domains and develop and deploy your own NTMA and VQA applications using JavaScript and Node.js. What You Will LearnWhat are the fundamental concepts, existing applications, and research on NTMA?What are the existing software and current research trends in VQA?Which machine learning algorithms are used in NTMA and VQA?How do you develop NTMA and VQA web-based applications using JavaScript, HTML, and Node.js? Who This Book Is ForSoftware professionals and machine learning engineers involved in the fields of networking and telecommunications.…

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Paperback. Condizione: New. Learn the United Nations Sustainable Development Goals (UN SDGs) and see how machine learning can significantly contribute to their realization. This book imparts both theoretical knowledge and hands-on experience in comprehending and constructing machine learning-based applications for addressing multiple UN SDGs using JavaScript. The reading begins with a delineation of diverse UN SDG targets, providing an overview of previous successful applications of machine learning in solving realistic problems aligned with these targets. It thoroughly explains fundamental concepts of machine learning algorithms for prediction and classification, coupled with their implementation in JavaScript and HTML programming.Detailed case studies examine challenges related to renewable energy, agriculture, food production, health, environment, climate change, water quality, air quality, and telecommunications, corresponding to various UN SDGs. Each case study includes related works, datasets, machine learning algorithms, programming concepts, and comprehensive explanations of JavaScript and HTML codes used for web-based machine learning applications. The results obtained are meticulously analyzed and discussed, showcasing the pivotal role of machine learning in advancing the relevant SDGs. By the end of this book, you'll have a firm understanding of SDG fundamentals and the practical application of machine learning to address diverse challenges associated with these goals.What You'll LearnUnderstand the fundamental concepts of the UN SDGs, AI, and machine learning algorithms.Employ the correct machine learning algorithms to address challenges on the United Nations Sustainable Development Goals (UN SDGs)?Develop web-based machine learning applications for the UN SDGs using Javascript, and HTML.Analyze the impact of a machine learning-based solution on a specific UN SDG.Who This Book Is ForData scientists, machine learning engineers, software professionals, researchers, and graduate students.…

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Paperback. Condizione: New. First Edition. This book offers both theoretical insights and hands-on experience in understanding and building machine learning-based Network Traffic Monitoring and Analysis (NTMA) and Video Quality Assessment (VQA) applications using JavaScript. JavaScript provides the flexibility to deploy these applications across various devices and web browsers. The book begins by delving into NTMA, explaining fundamental concepts and providing an overview of existing applications and research within this domain. It also goes into the essentials of VQA and offers a survey of the latest developments in VQA algorithms. The book includes a thorough examination of machine learning algorithms that find application in both NTMA and VQA, with a specific emphasis on classification and prediction algorithms such as the Multi-Layer Perceptron and Support Vector Machine. The book also explores the software architecture of the NTMA client-server application. This architecture is meticulously developed using HTML, CSS, Node.js, and JavaScript. Practical aspects of developing the Video Quality Assessment (VQA) model using JavaScript and Java are presented. Lastly, the book provides detailed guidance on implementing a complete system model that seamlessly merges NTMA and VQA into a unified web application, all built upon a client-server paradigm. By the end of the book, you will understand NTMA and VQA concepts and will be able to apply machine learning to both domains and develop and deploy your own NTMA and VQA applications using JavaScript and Node.js. What You Will LearnWhat are the fundamental concepts, existing applications, and research on NTMA?What are the existing software and current research trends in VQA?Which machine learning algorithms are used in NTMA and VQA?How do you develop NTMA and VQA web-based applications using JavaScript, HTML, and Node.js? Who This Book Is ForSoftware professionals and machine learning engineers involved in the fields of networking and telecommunications.…

Paperback. Condizione: New. Learn the United Nations Sustainable Development Goals (UN SDGs) and see how machine learning can significantly contribute to their realization. This book imparts both theoretical knowledge and hands-on experience in comprehending and constructing machine learning-based applications for addressing multiple UN SDGs using JavaScript. The reading begins with a delineation of diverse UN SDG targets, providing an overview of previous successful applications of machine learning in solving realistic problems aligned with these targets. It thoroughly explains fundamental concepts of machine learning algorithms for prediction and classification, coupled with their implementation in JavaScript and HTML programming.Detailed case studies examine challenges related to renewable energy, agriculture, food production, health, environment, climate change, water quality, air quality, and telecommunications, corresponding to various UN SDGs. Each case study includes related works, datasets, machine learning algorithms, programming concepts, and comprehensive explanations of JavaScript and HTML codes used for web-based machine learning applications. The results obtained are meticulously analyzed and discussed, showcasing the pivotal role of machine learning in advancing the relevant SDGs. By the end of this book, you'll have a firm understanding of SDG fundamentals and the practical application of machine learning to address diverse challenges associated with these goals.What You'll LearnUnderstand the fundamental concepts of the UN SDGs, AI, and machine learning algorithms.Employ the correct machine learning algorithms to address challenges on the United Nations Sustainable Development Goals (UN SDGs)?Develop web-based machine learning applications for the UN SDGs using Javascript, and HTML.Analyze the impact of a machine learning-based solution on a specific UN SDG.Who This Book Is ForData scientists, machine learning engineers, software professionals, researchers, and graduate students.…

Soft cover. Condizione: New. ISBN:9781032937939,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

paperback. Condizione: Good. Minimal creasing on cover/spine. Pages are clean.

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Condizione: As New. Unread book in perfect condition.

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Paperback. Condizione: New. 1. The item is brand new, never used or read. It's in perfect condition and may include supplements and/or access codes or come shrink-wrapped.

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