design intelligent applications using (32 resultados)

Condición: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. Print on Demand.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. 1st edition NO-PA16APR2015-KAP.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New. In.

Paperback. Condición: Brand New. 446 pages. 10.00x7.00x10.00 inches. In Stock.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New. In.

Condición: New.

Hardcover. Condición: Brand New. 432 pages. 10.25x7.25x1.25 inches. In Stock.

Paperback. Condición: new. Paperback. Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction. Apart from these domains, ML and DL are found useful in analysing the social behaviour of humans. With the advancements in the amount and type of data available for use, it became necessary to build a means to process the data and that is where deep neural networks prove their importance. These networks are capable of handling a large amount of data in such fields as finance and images. This book also exploits key applications in Industry 4.0 including: Fundamental models, issues and challenges in ML and DL. Comprehensive analyses and probabilistic approaches for ML and DL. Various applications in healthcare predictions such as mental health, cancer, thyroid disease, lifestyle disease and cardiac arrhythmia. Industry 4.0 applications such as facial recognition, feather classification, water stress prediction, deforestation control, tourism and social networking. Security aspects of Industry 4.0 applications suggest remedial actions against possible attacks and prediction of associated risks. - Information is presented in an accessible way for students, researchers and scientists, business innovators and entrepreneurs, sustainable assessment and management professionals.This book equips readers with a knowledge of data analytics, ML and DL techniques for applications defined under the umbrella of Industry 4.0. This book offers comprehensive coverage, promising ideas and outstanding research contributions, supporting further development of ML and DL approaches by applying intelligence in various applications. This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It is about Intelligent Bike using AI based on riding conditions. It is able to collect and transmit multiple sensor data to the cloud database, and the real -time sensor information is used to analyze for an appropriate riding state through random forest. Our performs automatic gear shifting using inexpensive sensor components and embedded system development board, which is not available in current expensive electronic shifting systems.The function and the installation of the external components can be carried out on the o-the-shelf bike with a shifting line, without the need to dismantle or modify the basic equipment. The system also includes an Intelligent bike specific online management interface that allows all cloud data to be displayed and let users access and understand their riding conditions.

Paperback. Condición: new. Paperback. Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction. Apart from these domains, ML and DL are found useful in analysing the social behaviour of humans. With the advancements in the amount and type of data available for use, it became necessary to build a means to process the data and that is where deep neural networks prove their importance. These networks are capable of handling a large amount of data in such fields as finance and images. This book also exploits key applications in Industry 4.0 including: Fundamental models, issues and challenges in ML and DL. Comprehensive analyses and probabilistic approaches for ML and DL. Various applications in healthcare predictions such as mental health, cancer, thyroid disease, lifestyle disease and cardiac arrhythmia. Industry 4.0 applications such as facial recognition, feather classification, water stress prediction, deforestation control, tourism and social networking. Security aspects of Industry 4.0 applications suggest remedial actions against possible attacks and prediction of associated risks. - Information is presented in an accessible way for students, researchers and scientists, business innovators and entrepreneurs, sustainable assessment and management professionals.This book equips readers with a knowledge of data analytics, ML and DL techniques for applications defined under the umbrella of Industry 4.0. This book offers comprehensive coverage, promising ideas and outstanding research contributions, supporting further development of ML and DL approaches by applying intelligence in various applications. This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction. Apart from these domains, ML and DL are found useful in analysing the social behaviour of humans. With the advancements in the amount and type of data available for use, it became necessary to build a means to process the data and that is where deep neural networks prove their importance. These networks are capable of handling a large amount of data in such fields as finance and images. This book also exploits key applications in Industry 4.0 including: Fundamental models, issues and challenges in ML and DL. Comprehensive analyses and probabilistic approaches for ML and DL. Various applications in healthcare predictions such as mental health, cancer, thyroid disease, lifestyle disease and cardiac arrhythmia. Industry 4.0 applications such as facial recognition, feather classification, water stress prediction, deforestation control, tourism and social networking. Security aspects of Industry 4.0 applications suggest remedial actions against possible attacks and prediction of associated risks. - Information is presented in an accessible way for students, researchers and scientists, business innovators and entrepreneurs, sustainable assessment and management professionals.This book equips readers with a knowledge of data analytics, ML and DL techniques for applications defined under the umbrella of Industry 4.0. This book offers comprehensive coverage, promising ideas and outstanding research contributions, supporting further development of ML and DL approaches by applying intelligence in various applications. This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Ramchandra Mangrulkar have received his PhD in Computer Science and Engineering from SGBAU Amravati in 2016 and currently he is working as an Associate Professor at the department of Computing Engineering at DJSCE Mumbai, Maharashtra, India. Prior to.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.