This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social … adage "once you understand OLS, you can work your way up to any other estimator," and apply it to Machine Learning. Focusing … and fire some trailblazers to the forefront of AI and causal machine learning. …

cognitive and analytical skills for problem-solving, including Machine Learning, Neural Networks, and Deep Learning" (p.443) …

names. We document that one explanation for this finding is that if an algorithm receives in real time less data about one … group, it will learn at different speeds. Since black names are less common, the algorithm learns about the quality of the … black names even if the algorithm judges the ad to be of low-quality. We extend this result by presenting evidence that ads …

for behavioral observational learning in social networks. We show that a seller could potentially control the information … available to future customers and induce behavioral observational learning by using an information-revealing pricing strategy … networks. It could prevent the behavioral observational learning that would increase future customers' willingness to pay …