Data Science Challenges Applications (63 results)

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Condition: Used. pp. 115.

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Condition: New. Editor(s): Simmons, Maryann. Num Pages: 115 pages. BIC Classification: GPJ; UNA; UTF; UTN. Category: (P) Professional & Vocational. Dimension: 160 x 233 x 15. Weight in Grams: 376. . 2015. Hardcover. . . . .

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Condition: As New. Unread book in perfect condition.

Condition: New. Editor(s): Simmons, Maryann. Num Pages: 115 pages. BIC Classification: GPJ; UNA; UTF; UTN. Category: (P) Professional & Vocational. Dimension: 160 x 233 x 15. Weight in Grams: 376. . 2015. Hardcover. . . . . Books ship from the US and Ireland.

Condition: New. In English.

Condition: New. 2022. 1st Edition. Hardcover. . . . . .

Gebunden. Condition: New. Sachi Nandan Mohanty, PhD, received his doctorate from IIT Kharagpur in 2015 and his PostDoc from IIT Kanpur in 2019. He has recently joined as an associate professor at VIT-AP University, Andhra Pradesh. He has edited 24 books and published more than 100 r.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science.Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field.In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energymanagement, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.…

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science.Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field.In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energymanagement, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.…

Hardcover. Condition: Brand New. 352 pages. 9.29x6.22x0.98 inches. In Stock.

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Paperback. Condition: Brand New. 332 pages. 9.25x6.10x0.78 inches. In Stock.