State of Data #104

Top Read – Casino’s Data Cloud

“Let’s say we want to see the profitability of females fifty-five and older. Who are these ladies? Where do they live? How can we target them better?” The representative showed an animated map of an unidentified city, titled “ground floor, little old ladies, carded play time.” As the clock in the upper left-hand corner spun, the city flared and pulsed with color, registering the home addresses of older women gamblers as they began and ended sessions of machine play on the ground floor of one casino over the course of a day.


Why, statistically speaking, Bank robbery is a really bad idea

Big Data

Crunch commuter data to find ‘a community’s prosperity is reflected in the comings and goings of its residents’ (original paper)


Data Science

Large scale Machine Learning at Twitter (Original Paper)
“There are three main components of a machine learning solution: the data, features extracted from the data, and the model. Accumulated experience over the last decade has shown that in real-world settings, the size of the dataset is the most important factor. Studies have repeatedly shown that simple models trained over enormous quantities of data outperform more sophisticated models trained on less data.”



2-page, brief introduction to Eventual Consistency (pdf)



Learn Pi with Matchsticks



Doing the Line Charts Right with Best Representation of Facebook’s IPO day



Civil War visualized with Python

‘In this view, which my friend Evan Sheehan has termed “ball pit visualization,” each battle would have been represented as a pie chart dropped into a “pit.” Each pit would correspond to who had won the battle.’




About Nilendu Misra
I love to learn, create and coach. Things that I do well are - Communicating ideas - verbally or through words and diagrams; Problem Solving - Logical or Abstract; Very Large Scale Systems; think about 'Frighteningly Simple' approach first. Things that I intend to do better are - Establishing Stringent Process; Exchanging Tough Feedback; Keeping up with my reading or To-Do list to be able to completely relax.

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