Introduction to Artificial Neural Networks and Machine Learning

This chapter presents a methodology for introducing artificial neural networks (ANNs) and machine learning (ML) algorithms in K–12 STEM-driven CS education. The content of this chapter consists of the following topics: (i) overview of the operating tasks (research questions) and proposed methodology (RQ1), (ii) background with a definition of basic terms and models related to ANNs and ML (RQ2), (iii) motivating example and its ML algorithm (with manual implementation) for the initial understanding of the area of ANNs (RQ3), and (iv) development and implementation of two case studies (RQ4). Both include multiple tasks. Those cover single-layered and multi-layered perceptron models with a thorough description of the experimental work we have carried out with those models.