Hybrid Imaging and Visualization
Employing Machine Learning with Mathematica - Python
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90 774 Ft (86 451 Ft + 5% VAT)
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90 774 Ft
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Product details:
- Edition number Second Edition 2025
- Publisher Springer
- Date of Publication 2 June 2025
- Number of Volumes 1 pieces, Book
- ISBN 9783031728167
- Binding Hardback
- No. of pages450 pages
- Size 235x155 mm
- Language English
- Illustrations 73 Illustrations, black & white; 481 Illustrations, color 700
Categories
Short description:
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.
MoreLong description:
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.
MoreTable of Contents:
Chapter 1. Dimension Reduction.- Chapter 2. Classification.- Chapter 3. Clustering.- Chapter 4. Regression.- Chapter 5. Neural Networks.- Chapter 6. Optimizing Hyperparameters.- Chapter 7. ChatGPT.
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