Thoughts on data science, statistics and machine learning.

Book Review: To a God Unknown - John Steinbeck

In Journal of a Novel: The East of Eden Letters, Steinbeck wrote that reading books is like driving a wedge in your life. The larger the wedge, the harder it is for parts to come together once the wedge is removed. The longer the book, the harder it is to close the mental gap around it. Steinbeck wrote this for East of Eden - his magnum opus. Surprisingly, this happens even with Steinbeck’s much shorter books.

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Book Review: Treasure Island - R L Stevenson

There are stories you know well but you never really read well. Captain Flint (the man and the parrot), Jim Hawkins, Long John Silver and Billy Bones, the Old Sea Dog are immortal characters, without a touch of age upon them or their story. Treasure Island was perhaps the first classic I actually skimmed through many times in my childhood. I didn’t read it in earnest until now, and I did that because the final season of Black Sails is about to end.

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Rabies, Laziness & Privilege

It was the night of the recent 5-state assembly elections. One of my company’s clients is a major news channel, and I was at the studio late into the night, until the election commission announced that they had cancelled their press conference which was supposed to make an announcement about the final vote counts in Madhya Pradesh. A colleague offered to drop me home, and I got off at the gate of my colony, not wanting to subject my colleague to navigating the labyrinth that is any gated colony in South Delhi.

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Weighted Loss Functions for Instance Segmentation

This post is a follow up to my talk, Practical Image Classification & Object Detection at PyData Delhi 2018. You can watch the talk here: and see the slides here. I spoke at length about the different kinds of problems in computer vision and how they are interpreted in deep learning architectures. I spent a fair bit of time on instance and semantic segmentation (for an introduction to these problems, watch Justin Johnson’s lecture from the Stanford CS231 course here).

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