First known article by any renowned economist that focused on machine learning (and big data) was published in 2014 (Big Data: New Tricks for Econometrics by H. R. Varian). He introduced some applications of machine learning techniques such as decision trees, support vector machines, neural nets, and deep learning which allow for more effective ways to model complex relationships.
I believe that these methods have a lot to offer and should be more widely known and used by economists.
Here I will try my best to made a walk in through guide for the economists who are interested in machine learning. It should consists of some introductory concepts related to machine learning and mainly a guidelines for the new comers to this machine learning world (like me).
- Applications in economics
- Learning Machine Learning: Python Vs R
- Free resources for learning machine learning
- Where to start?