TY - JOUR T1 - Machine Learning for Structured Finance JF - The Journal of Structured Finance SP - 7 LP - 25 DO - 10.3905/jsf.2018.24.3.007 VL - 24 IS - 3 AU - Eric Kolchinsky Y1 - 2018/10/31 UR - https://pm-research.com/content/24/3/7.abstract N2 - Machine learning and artificial intelligence have evolved beyond simple hype and have integrated themselves in business and in popular conversation as an increasing number of smart applications profoundly transform the way we work and live. This article defines machine learning in terms of potential benefits and pitfalls for a nontechnical audience, and gives examples of popular and powerful machine learning algorithms: k-means clustering, principal component analysis, and artificial neural networks. Three important philosophical challenges of machine learning are introduced: the no free lunch theorem, the curse of dimensionality, and the bias–variance trade-off.TOPICS: Big data/machine learning, statistical methods ER -