Implementations and Applications of Machine Learning (Record no. 75251)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04545nam a22006375i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-37830-1 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801213512.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200423s2020 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783030378301 |
| -- | 978-3-030-37830-1 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 621.382 |
| 245 10 - TITLE STATEMENT | |
| Title | Implementations and Applications of Machine Learning |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XII, 280 p. 120 illus., 92 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Studies in Computational Intelligence, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Part 1: Machine learning concepts, methods, and software tools -- Overview -- Classifying algorithms -- Support vector machines -- Bayes classifiers -- Decision trees -- Clustering algorithms -- k-means and variants -- Gaussian mixture -- Association rules -- Optimization algorithms -- Genetic algorithms -- Swarm intelligence -- Deep learning,- Convolutional neural networks (CNN) -- Other deep learning schema -- Part 2: Applications with implementations -- Protein secondary structure prediction -- Mapping heart disease risk -- Surgical performance monitoring -- Power grid control -- Conclusion. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning. Presents practical, useful applications of machine learning for practitioners, students, and researchers Provides hands-on tools for a variety of machine learning techniques Covers evolutionary and swarm intelligence, facial and image recognition, deep learning, data mining and discovery, and statistical techniques. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Subair, Saad. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Thron, Christopher. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-030-37830-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2020. |
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| -- | text |
| -- | txt |
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| 337 ## - | |
| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Telecommunication. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Dynamics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Nonlinear theories. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Medical informatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Communications Engineering, Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Applied Dynamical Systems. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Informatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 1860-9503 ; |
| 912 ## - | |
| -- | ZDB-2-ENG |
| 912 ## - | |
| -- | ZDB-2-SXE |
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