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A lot of discussion around the use of R and Python and similar languages assume they are implementing various ML/AI techniques on data. In this talk, we ignore all that, and focus on how to use these libraries to perform mundane tasks common to a lot of actuarial work.
Data munging, manipulation, tidying and linking is an overlooked but vital part of any data-centred work and in this talk we focus on those less glamorous parts of the job. In particular, we will use R and the tidyverse to model out the future cash flows from a sample bond portfolio allowing us to automate this work in the future.
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