In the last few weeks, I had to work on matching a large number of records relating to various companies with an internal feature rich dataset for 10 million companies. Needless to say, there were no readily available standardized identifiers across the two databases the one could perform a join operation. The record matching had to be based on approximate matching and probabilistic matching. Until this piece of work came along my way, I had never heard of “Record Matching” as a subject in itself where people do PhDs in.

Immersed myself in a quite a few papers, books and blogposts to understand this field just enough so that I can get my work done. In the process I found several interesting talks, books, decks, papers. Hopefully in the days to come, I will try to summarize a few papers and books. This post summarizes a series of posts written by Robin Linacre, who works in Ministry of Justice UK.

shiny is my goto package for building interactive dashboard. I have built more than fifty shiny apps so far and have found the entire package infrastructure around it to be extremely useful in showcasing data, algos, metrics - you name it. This book by Hadley Wickham came out in 2021 but I never had a chance to go over it, until now. It was wonderful to see so many code patterns/hacks that I have learned over years appearing in the book. Needless to say, I have learned so many fascinating aspects of shiny from this book. This blogpost summarizes some of my learnings/relearnings from the book:

Had a chance to attend Crypt Asia 2023 held at Singapore. Here are some random set of notes from the event

Chanced upon a wonderful presentation by Jennifer Bryan on debugging in R

This blogpost is a brief summary of the book titled, “Central Banking 101”, written by Joseph Wang.