… to symbolic machine learning, to recent techniques for learning relational concepts. In this
… suitable for software engineering applications, including inductive program development, …

… 1–3, which introduces the basics of machine learning. The second part includes Chapters
4–10, which presents some classic and popular machine learning methods. The third part …

… algorithms assume that a dataset is available for training; and in Chapter 3 we explain how
to design, construct, and quality check a dataset before using it to build a prediction model. …

… Deep learning is a machine learning concept based on … , deep learning models outperform
shallow machine learning … the fundamentals of machine learning and deep learning to …

… You don’t need previous experience with machine learning or deep learning: this book
covers, from scratch, all the necessary basics. You don’t need an advanced mathematics …

… Chapter 2 introduces the basics of machine learning and discusses how it relates to model
… in software engineering, first we decide on the requirements, then we go down one step and …

… in machine learning, especially with regard to deep learning, are … Deep learning is rapidly
becoming the state of the art, … We introduce the fundamentals of deep learning methods and …

… First, in Section 2, we discuss the basis of this area, which we call the “naturalness hy…
Then we describe the software engineering and programming language applications of …

… software engineering is to provide models and techniques that make it easier to handle this
complexity [46,54]. To this end, a wide range of software engineering … The basis for this belief …

… Machine learning offers a fantastically powerful toolkit for building useful complex prediction
… Using the software engineering framework of technical debt, we find it is common to incur …