Datacast
Episode 27: Feature Engineering with Ben Fowler
Episode Summary
Ben Fowler has been in the field of data science for over five years. In his current role at Southeast Toyota Finance, Ben leads the end to end model development process to solve the problem of interest. Ben holds a Master of Science in Data Science from Southern Methodist University, graduating in 2017. Following graduation, Ben has been a guest speaker to the SMU program multiple times. Additionally, Ben has spoken at the PyData Miami 2019 and PyData LA 2019 Conferences and has spoken multiple times at the West Palm Beach Data Science Meetup.
Episode Notes
Show Notes:
- (2:17) Ben talked about his past career working in the golf industry - working at the National Golf Foundation and the PGA of America.
- (4:12) Ben discussed about his first exposure to machine learning and data science.
- (5:06) Ben talked about his motivation for pursuing an online Master’s degree in Data Science at Southern Methodist University.
- (6:02) Ben emphasized the importance of a Data Mining course that he took.
- (8:12) Ben discussed his job as a Senior Data Scientist at CarePredict, an AI elder care platform that helps senior live independently, economically, and longer.
- (8:56) Ben shared his thought about data security, the biggest challenge of adopting machine learning in healthcare.
- (10:38) Ben talked about his next employer JM Family Enterprises, one of the largest companies in the automotive industry.
- (12:44) Ben walked through the end-to-end model development process to solve various problems of interests in his Data Scientist work at JM Family Enterprises.
- (14:15) Ben discussed the challenges around feature engineering and model experiments in this process.
- (18:09) Ben shared information about his current role as Machine Learning Technical Lead at Southeast Toyota Finance.
- (19:29) Ben talked about his passion to do IC data science work.
- (22:37) Ben went over different conferences he has been / will be at.
- (26:03) Ben shared the best practices/techniques/libraries to do efficient feature engineering and feature selection, as presented at Palm Beach Data Science Meetup in September 2018 and PyData Miami in January 2019.
- (29:27) Ben talked about the importance of doing exploratory data analysis and logging experiments before engaging in any feature engineering / selection work.
- (32:50) Ben shared his experiments performing data science for Fantasy Football - specifically using machine learning to predict the future performance of players, from his talk at the Palm Beach Data Science Meetup last year.
- (37:25) Ben talked about his experience using H2O AutoML.
- (40:07) Ben gave a glimpse of his talks about evaluating traditional and novel feature selection approaches at PyData LA and Strata Data Conf.
- (51:25) Ben gave his advice for people who are interested in speaking at conferences.
- (52:29) Ben shared his thoughts about the tech and data community in the greater Miami area.
- (53:16) Closing Segment.
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