A concise introduction to machine learning / A.C. Faul.
By: Faul, A. C. (Anita C.) [author.].
Series: Chapman & Hall/CRC machine learning & pattern recognition series.Publisher: Boca Raton : CRC Press, Taylor & Francis Group, ©2020Description: xix, 314 pages : illustrations ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780815384205; 9780815384106.Subject(s): Machine learning -- TextbooksGenre/Form: Print books.Summary: "Machine Learning is known by many different names, and is used in many areas of science. It is also used for a variety of applications, including spam filtering, optical character recognition, search engines, computer vision, NLP, advertising, fraud detection, robotics, data prediction, astronomy. Considering this, it can often be difficult to find a solution to a problem in the literature, simply because different words and phrases are used for the same concept. This class-tested textbook aims to alleviate this, using mathematics as the common language. It covers a variety of machine learning concepts from basic principles, and llustrates every concept using examples in MATLAB"--| Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|
| On Shelf | Q325.5 .F38 2020 (Browse shelf) | Available | AU00000000018760 |
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| Q325.5 .D45 2020 Mathematics for machine learning / | Q325.5 .E36 2022 Learning deep learning : theory and practice of neural networks, computer vision, nlp, and transformers using tensorflow / | Q325.5 .E87 2020 Introducing machine learning / | Q325.5 .F38 2020 A concise introduction to machine learning / | Q325.5 .F43 2018 Feature engineering for machine learning and data analytics / | Q325.5 .F67 2019 Generative deep learning : teaching machines to paint, write, compose, and play / | Q325.5 .F67 2023 Generative deep learning : teaching machines to paint, write, compose, and play / |
"A Chapman & Hall book."
Includes bibliographical references (pages 301-303) and index.
"Machine Learning is known by many different names, and is used in many areas of science. It is also used for a variety of applications, including spam filtering, optical character recognition, search engines, computer vision, NLP, advertising, fraud detection, robotics, data prediction, astronomy. Considering this, it can often be difficult to find a solution to a problem in the literature, simply because different words and phrases are used for the same concept. This class-tested textbook aims to alleviate this, using mathematics as the common language. It covers a variety of machine learning concepts from basic principles, and llustrates every concept using examples in MATLAB"--