9780367649111 - Prediction and Analysis for Knowledge Representation and Machine Learning (15 resultados)

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Condición: New. pages cm First edition Includes bibliographical references and index.

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Paperback. Condición: Brand New. 232 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Condición: new. Paperback. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the systems perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the books website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts. This book illustrates different techniques and structures that are used in knowledge representation and machine learning. The aim of this book is to draw the attention of graduates, researchers and practitioners working in field of information technology and computer science (in knowledge representation in machine learning). This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.

Paperback. Condición: new. Paperback. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the systems perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the books website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts. This book illustrates different techniques and structures that are used in knowledge representation and machine learning. The aim of this book is to draw the attention of graduates, researchers and practitioners working in field of information technology and computer science (in knowledge representation in machine learning). This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condición: Neu. Prediction and Analysis for Knowledge Representation and Machine Learning | Avadhesh Kumar (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9780367649111 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book illustrates different techniques and structures that are used in knowledge representation and machine learning. The aim of this book is to draw the attention of graduates, researchers and practitioners working in field of information technology and computer science (in knowledge representation in machine learning).