| Valentina Grouverman, Lindzee Smith |
Statistical modeling is a significant part of data scientists' work as well as many SAS programmers. In the past we used mostly SAS and relied on its standard procedures as regressions. Now Python can provide us additional functionality and flexibility. Its compatibility with most cloud platforms and continuously increasing number of libraries and packages available for data analysis, modeling and machine learning made Python an ideal choice for statistical modeling in cloud environments. This article illustrates how SAS and Python can complement each other in model's development when we can effortlessly switch between these languages and see benefits of this adaptable approach. |