A Few Useful Things to Know about Machine Learning
Communications of the ACM, 55 (10):
78--87 (October 2012)DOI: 10.1145/2347736.2347755
Abstract
Tapping into the 'folk knowledge' needed to advance machine learning applications. Machine learning algorithms can figure out how to perform important tasks by generalizing from examples. This is often feasible and cost-effective where manual programming is not. As more data becomes available, more ambitious problems can be tackled. Machine learning is widely used in computer science and other fields. However, developing successful machine learning applications requires a substantial amount of 'black art' that is difficult to find in textbooks. This article summarizes 12 key lessons that machine learning researchers and practitioners have learned. These include pitfalls to avoid, important issues to focus on, and answers to common questions.
