| Description |
1 online resource (xiv, 214 pages) : illustrations (chiefly color), color map. |
| Series |
Advances in data science and computing technologies
|
| Bibliography |
Includes bibliographical references and index. |
| Summary |
"Machine learning is a vital part of numerous academic and financial applications, in areas ranging from health care and treatment to finding relevant information in social networks. Large organizations thoughtfully apply machine learning algorithms with extensive research teams. The purpose of this book is to provide an intellectual introduction to statistical or machine learning (ML) techniques for those that would not normally be exposed to such approaches during their typical required statistical exercise. Statistical analysis is an integral part of machine learning and can be described as a form of it, often even utilizing well-known and familiar techniques, that has a different focus than traditional analytical practice in applied disciplines. The key notion is that flexible, automatic approaches are used to detect patterns within the data, with a primary focus on making predictions on future data"-- Provided by publisher. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Engineering -- Data processing.
|
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Artificial intelligence.
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Machine learning.
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artificial intelligence. |
|
Artificial intelligence |
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Engineering -- Data processing |
|
Machine learning |
| Added Author |
Chatterjee, Prasenjit, 1982- editor. https://id.oclc.org/worldcat/entity/E39PBJj4tfp3rWW4WkWdFr4H4q
|
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Astya, Parmanand, editor.
|
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Chakraborty, Sudeshna, editor.
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Pooja, editor.
|
| Other Form: |
Print version: Machine learning algorithms for engineering applications New York : Nova Science Publishers, [2022] 9781685074494 (DLC) 2022028067 |
| ISBN |
9798886970869 (electronic bk.) |
|
9781685074494 hardcover |
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