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. This book also highlights semiconductor materials and their uses in multi-gate devices, analog and Radio Frequency (RF) behaviour of semiconductor devices with different materials.

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This book is aimed at researchers and graduate students in semiconductor materials, machine learning, and electrical engineering.