Buch

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Übersicht

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Verlag	:	Springer International Publishing
Buchreihe	:	The Springer Series in Applied Machine Learning
Sprache	:	Englisch
Erschienen	:	16. 03. 2024
Seiten	:	358
Einband	:	Kartoniert
Höhe	:	235 mm
Breite	:	155 mm
ISBN	:	9783031023651
Sprache	:	Englisch
Illustrationen	:	XX, 358 p. 233 illus., 132 illus. in color.

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Autorinformation

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Poornachandra Sarang, in his IT career spanning four decades, has been consulting large IT organizations on the design and architecture of systems using state-of-the-art technologies. He has authored several books covering a wide range of emerging technologies. Dr. Sarang is a Ph.D. advisor for Computer Science and Engineering and is on the thesis advisory committee for aspiring doctoral candidates. He has designed and delivered courses/curricula for universities at the postgraduate level, including courses and workshops on emerging technologies for industry. He is a known face at technical and research conferences delivering both keynote and technical talks.

Inhaltsverzeichnis

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Chapter. 1. Data Science Process.- Chapter. 2. Dimensionality Reduction - Creating Manageable Training Datasets.- Chapter. 3. Classical Algorithms - Over-view.- Chapter. 4. Regression Analysis.- Chapter. 5. Decision Tree.- Chapter. 6. Ensemble - Bagging and Boosting.- Chapter. 7. K-Nearest Neighbors.- Chapter. 8. Naive Bayes.- Chapter. 9. Support Vector Machines: A supervised learning algorithm for Classification and Regression.- Chapter. 10. Clustering Overview.- Chapter. 11. Centroid-based Clustering.- Chapter. 12. Connectivity-based Clustering.- Chapter. 13. Gaussian Mixture Model.- Chapter. 14. Density-based.- Chapter. 15.- BIRCH.- Chapter. 16. CLARANS.- Chapter. 17. Affinity Propagation Clustering.- Chapter. 18. STING.- Chapter. 19. CLIQUE.- Chapter. 20. Artificial Neural Networks.- Chapter. 21. ANN-based Applications.- Chapter. 22. Automated Tools.- Chapter. 23. DataScientist’s Ultimate Workflow.

Deine Buchhandlung

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