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What every new writer on Medium can learn from this single verse of the Bhagavad Gita.

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The Bhagavad Gita is one of the greatest spiritual books ever written.

This hyperbole is completely justified for this book, purely based on the number of discussion, debates, adaptations and interpretations that it has spawned.

This post is not intended to extoll the virtues of this book.

Neither is it a propaganda piece for any religion.

This post is simply concerned with only three pieces of knowledge, gleamed from this book.

One of the most profound and perhaps most famous verse from The Gita…

Photo by Esteban Lopez on Unsplash

I lie. A lot.

There I said it.

But that’s not the whole story.

I lie to save people.

‘Nah babe, that dress doesn’t make you look fat, it just accentuates your natural curves’ (But maybe you should join me in the gym from tomorrow)

Hey no problem, your kids are so intelligent and energetic that I didn’t even realise the night go by! (Yeah, I won’t be baby-sitting them any time soon…even if you paid me by the minute, Oh Brother of mine)

‘Listen buddy, it’s alright. You parked the car well and drove with discipline. I’m proud of…

Photo by Nathan Duck on Unsplash

I looked at the tiny mole on the junction of my wife’s pinkie and index finger. It was where it had always been. A reminder that she was the One.

‘Could you let go of my hand, Joe?’

I looked up, my fingers still intertwined with hers. The street lamp behind us illuminated half her face and it was the same one I had always known.

‘Joe, your hands are sweating and its fucking disgusting’.

I slowly released my grip and saw her hurriedly wipe her hands down her jeans. She had this look of mild irritation and disgust on…

Photo by Clem Onojeghuo on Unsplash

A high level overview of this multi-criteria decision making method along with a use-case.


Through the course of a lifetime, a human makes a number of decisions, ranging from the most trivial ones that have almost no impact, to those that have life changing consequences. And almost always, these situations involve X number of options and Y number of criteria that they are judged on.

Photo by Mike Kenneally on Unsplash

Data Science

Using Empirical Mode Decomposition to understand wholesale prices of my favorite beverages!


My mornings usually begin with a mug of steaming black coffee. No, it’s not the expensive gourmet stuff, but the instant coffee powder that powers me through the rest of the morning.

My evenings are usually more mellow, with a nice cup of strong Indian tea and perhaps a couple of biscuits. They provide just the right amount of caffeine to make it all the way to 10 pm.


I recently had to use a nifty signal processing tool — Empirical Mode Decomposition (EMD)— at work and thought this would make for an interesting post!

In this article, I would…

Photo by Julian Hochgesang on Unsplash

Kyung-Soon started walking up the trail as fast her tired feet could take her. Sweat trickled down the nape of her slender neck and slid down her spine, giving her a little shiver of uneasiness. Every laboured breath she took came out as puffs of vapour that was lost in the fog around her. All she could see was the dark, muddy path a few feet ahead, before it disappeared into the waiting fog.

She gave the strap of her rucksack a nervous tug, as if it were the only solid, reassuring object around her. She kept glancing at her…

Photo by Jair Lázaro on Unsplash

The second part of the step-by-step walk-through to analyze and predict the survival of heart failure patients.


In the previous post, we looked at the heart failure dataset of 299 patients, which included several lifestyle and clinical features. That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models.


The motivating question is— ‘What are the chances of survival of a heart failure patient?’. Through this walk-through, I try to answer this question while also giving a few insights on dealing with imbalanced datasets.

The code for this project can be found on my GitHub repository.

Quick Recap

In the previous post, we saw that —

  • Age and serum creatinine had a…

Source: Wallpaper Cave

Data Science, Machine Learning

A step-by-step pythonic walk-through of the analysis of survival data along with a domain-level explanation.


Cardiovascular diseases are diseases of the heart and blood vessels and they typically include heart attacks, strokes, and heart failures [1]. According to the World Health Organization (WHO), cardiovascular diseases like ischaemic heart disease and stroke have been the leading causes of deaths worldwide for the last decade and a half [2].


A few months ago, a new heart failure dataset was uploaded on Kaggle. This dataset contained health records of 299 anonymized patients and had 12 clinical and lifestyle features. The task was to predict heart failure using these features.

Through this post, I aim to document my workflow…

Image by Free-Photos from Pixabay

Visually exploring historic airline accidents, applying frequentist interpretations and validating changing trends with PyMC3.


On the 7th of August this year, an Air India Express flight on a repatriation mission from Dubai (United Arab Emirates) to Kozhikode (Kerala, India) skidded off the runway under heavy rainfall and fell into a valley [1].

The ensuing 35 foot drop broke the aircraft into two. The flight was ferrying a total of 180 souls and 18 of them lost their lives as an immediate consequence of the accident. The remaining 172 were injured to varying degrees and underwent treatment [2].

The official probe…

Top 200 words in the last 21 years of independence day speeches in India (credit: author)

EDA of 21 years of Indian Independence day speeches and predicting speech length for 15 August 2020


A few days ago I was sitting in my apartment and contemplating this question — “Will this Independence Day be any different than the last?

Of course it will. For obvious reasons.

And that question led me to another question — “Knowing that it will be different, what will the Prime Minister say this time?

That is the one thing that nearly a billion people around the country would be eagerly waiting to hear.

Because this year we have faced odds and seen tragedy on a scale never seen before in the recent past. …

Anirudh Chandra

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