Shulph Ink
Machine Learning for Semiconductor Materials
Machine Learning for Semiconductor Materials
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- More about Machine Learning for Semiconductor Materials
Format: Hardback
Length: 208 pages
Publication date: 21 August 2025
Publisher: Taylor & Francis Ltd
Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of Technology Computer Aided Design (TCAD). It provides the various algorithms of machine learning such as regression, decision tree, support vector machine and k-means clustering and so forth.
Weight: 580g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032796888
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