ABSTRACT
This chapter examines the various classification tasks and techniques along with various potential applications of machine learning-based classification techniques in ALD and thin film deposition. It also examine a number of case studies from the literature where the classification techniques of supervised machine learning methods have been successfully used to improve ALD process and thin film deposition and materials. Machine learning-based classification techniques in ALD have a wide range of potential applications. Common classifier's algorithms used for classification task in machine learning are multilayer perceptron or extreme learning machine, support vector machine, Naive Bayes, random forest, decision tree, and logistic regression. The chapter investigates the predictive analysis part of the neural network, while its classification task is the focus of this chapter. The ALD process was then optimized for the SE of TiO2 substrates as a way for the authors to show how their machine learning-based SE model may be used in practice.
