Python is a very popular coding language for doing predictive modeling and data science. We have been discussing python as part of our ongoing Predictive Analytics podcast series for the Society of Actuaries. Four episodes are available for listening now:
This is the first of a few podcasts focused on Python, a popular tool for predictive modeling and machine learning. In this episode, join Anders Larson, FSA, MAAA and Shea Parkes, FSA, MAAA as they cover some basics and talk about when Python may be a good idea to try.
Join hosts Anders Larson, FSA, MAAA, and Shea Parkes, FSA, MAAA, for the second in a series of podcasts focused on Python. After giving an introduction to the popular programming language in our previous episode, they discuss some key concepts in Python, such as its object-oriented framework, the idea of namespaces, the ability to create package sets and a few other topics.
Join hosts Anders Larson, FSA, MAAA, and Shea Parkes, FSA, MAAA, for the third in a series of podcasts focused on Python. Moving on from the foundational concepts and background from the prior two episodes, this episode moves into more practical advice for actuaries looking to get started with Python. The discussion includes pros and cons of various editing software and user interfaces. To provide some useful context, Shea also discusses the key considerations that his own team made as they implemented Python into their operations.
Join hosts Anders Larson, FSA, MAAA, and Shea Parkes, FSA, MAAA, for the fourth in a series of podcasts focused on Python. The previous episode covered how to get started with Python. This episode covers useful packages for data analysis. Python is a general purpose language at heart, so you will likely need to use a variety of packages to perform most data science tasks. Luckily, the Python ecosystem is full of feature-rich data science packages. Listen to this episode to learn about some of the most important ones.
The full backlog of podcasts in this Predictive Analytics series is available here (and on Stitcher etc).