Taking R From Hours to Seconds by Jared P. Lander. Visit [ Ссылка ] to learn more.
Abstract:
When facing a problem on a few millions rows of data, Jared wrote code that took hours to run, if at all. To speed things up he first split the data into smaller pieces, then did so in a smarter way. Still needing faster results, he wrote a custom function with a smarter algorithm, then sped it up further using Rcpp. All this took the runtime from hours to seconds, making it a feasible solution.
Bio:
Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York R Conference and an Adjunct Professor of Statistics at Columbia University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone, a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world. He is a member of the Strata New York selection committee. His writings on statistics can be found at jaredlander.com.
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Presented at the inaugural Government & Public Sector R Conference | New York (December 3, 2020)
