Machine learning is a growing field in the hospitality and tourism industry with undeniable potential. Yet, the topic in the hospitality literature is still emerging, and scholars have been calling for more theoretical research. What is particularly missing, according to academics, is a well-grounded machine learning theory specifically tailored to hospitality management. This paper aims to partially fill that gap by providing a practical introduction to machine learning for hospitality and tourism students and researchers new to the field. In the first part, the article presents the main theory behind machine learning and its terminology. In the second part, the paper presents a practical application of the theory via a case study. The case study shows unequivocally that machine learning is very efficient but requires a good understanding of the theory and this theory needs to be tailored specifically to hospitality and tourism.