Beer Flavor Analysis with Machine Learning Models

This chapter explores the use of machine learning models in connecting chemical data to sensory data for beer flavor analysis, emphasizing the effectiveness of tree-based models in predicting aspects like bitterness, mouthfeel, and alcoholic taste. It discusses the comparison between machine learning and statistical models, simplifies the process of machine learning with decision trees, and highlights the importance of data preparation. The chapter also delves into the challenges of utilizing machine learning in predicting beer flavors and introduces explainer models to provide insights into predicting flavors accurately.