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Hybrid Imaging and Visualization : Employing Machine Learning with Mathematica - Python / by Joseph Awange, Béla Paláncz, Lajos Völgyesi

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Edition: 2nd ed. 2025Description: 1 Online-Ressource(XXIII, 450 p. 554 illus., 481 illus. in color.)ISBN:
  • 9783031728174
Subject(s): Additional physical formats: 9783031728167 | 9783031728181 | 9783031728198 | Erscheint auch als: 9783031728167 Druck-Ausgabe | Erscheint auch als: 9783031728181 Druck-Ausgabe | Erscheint auch als: 9783031728198 Druck-AusgabeDDC classification:
  • 910.285 23
DOI: DOI: 10.1007/978-3-031-72817-4Online resources: Summary: Chapter 1. Dimension Reduction -- Chapter 2. Classification -- Chapter 3. Clustering -- Chapter 4. Regression -- Chapter 5. Neural Networks -- Chapter 6. Optimizing Hyperparameters -- Chapter 7. ChatGPT.Summary: This second edition of the book that targets those in computer algebra and artificial intelligence introduces Black Hole algorithm that is essential for optimizing hyperparameters, an important task in machine learning where mostly, stochastic global methods are used as well as ChatGPT, a novel and in the last few years, very popular Generative AI technology. In addition, fisher discriminant, a linear discriminant that can provide an optimal separation of objects, and the conversion of time series into images thereby making it possible to employ convolution neural network to classify time series effectively are presented.PPN: PPN: 1925485137Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-EES | ZDB-2-SXEE
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