Cubism meets machine learning
Machine Learning (ML) and Artificial Intelligence (AI) are well underway to becoming a staple in quantitative economics. Regularly, new fascinating applications hit national or international media. From AI outperforming doctors diagnosing breast cancer, over identifying dialects in naked mole rats to monitoring hiring discrimination, it seems no field is immune to the breakthroughs promised by AI. Similarly, a wide and expanding set of machine learning methods has been put forward. This poses challenges to researchers outside computer science wanting to incorporate such methods into their research.