Use simple, everyday examples to understand the fundamental concept so that you can even explain it to your grandmother.

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There is a lot of jargon that comes with data science and machine learning. Often, it takes a while to really understand some concepts that are often masked by formal definitions and mathematical equations. , according to Einstein,

“You do not really understand something unless you can explain it to your grandmother."

Maximum likelihood is one of the two fundamental approaches (the other being least squares estimation) to estimate parameters in machine learning and many new methods are inspired from these two.

Despite this, many courses and books explaining Maximum Likelihood fail to make it obvious that the technique is…


Free, Updated Introductory Course Delivered in 2021

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If you want to take your first few serious steps toward becoming an expert in deep learning, here is your opportunity!

They don’t come more easily (and for free) than this…

Perhaps the most well-known resource for learning deep learning is Andrew Ng’s series of 5 courses on . Those courses are still a great resource for anyone learning the fundamentals of the field but they are now a few years old (their launch was announced in ). In this post, I will give you three main reasons why you should instead start from MIT’s course that I am going to tell you about.

Before I try to convince you to start your deep learning journey from there, here is…


4 reasons why data science is here to stay and what you need to do to ensure that your skillset stays in demand.

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As someone working in data science for over a decade, it is frustrating to see people prophesying on how the field will get extinct in 10 years. The typical reason given is how emerging tools will eliminate the need for practitioners to develop their own algorithms.

I find such opinions especially frustrating because it dissuades a beginner from taking data science seriously enough to excel in it. Frankly, it is a disservice to the data science community to see such prophecies about a field where the demand is only going to increase even further!

Why would any sane person…

Key lessons and a practical system so that it doesn’t only make you feel good but instead inspires you to transform your productivity routine

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Until recently, I struggled with consistently staying productive. I have achieved phenomenal successes close to deadlines, but I never managed to keep momentum. Thanks to being in academia, I attended numerous courses and training workshops in the last 14 years to improve. However, at best, most of those have been only incrementally helpful. I even bought books on procrastination that I procrastinated on.

Despite these struggles, I always had a way of pulling things together last minute by dialing down on leisure, sleep, and social activities as and when required. This was possible because I was living alone. …

A case study based introduction to using Bayes rule and how it compares with a frequentist, pessimistic and optimistic approaches to drawing conclusions

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This post will help you understand Bayesian inference at an intuitive level with the help of a simple case study. I hope that once you read this article, you will be very clear on how the well-known “Bayes theorem” is used, what do the terms in the theorem mean (prior, posterior, likelihood) and how this compares with other approaches to decision making (pessimist /optimist/frequentist). We will use a simple case study to help explain the concepts. For those who are interested, I have provided simulation results for the given case study and a link to R code for further exploration…


Most data scientists are not even taught and remain unfamiliar with arguably the most useful supervised learning technique applied during the COVID-19 pandemic.

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Statistics and World War 2

To minimize bomber plane losses to enemy fire during World War 2, the US military wanted to armor the planes in places where they are most needed (identified as the points where the planes were the most damaged on return).

The challenge was to figure out the right amount of armor to put on. Too much would make the plane heavy leading to more fuel consumption and difficulty in maneuvering. Too little may not be sufficient to protect the plane.

To help with this, the military approached Abraham Wald (Hungarian Jewish mathematician, later to pioneer statistical sequential analysis). Wald gave…


Plain English explanation, and key assumptions to ensure you don’t get stumped in data science interviews

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Despite being amongst the few fundamental concepts in data science, the Central Limit Theorem (CLT) is still misunderstood.

Questions around such fundamental statistical concepts do pop up in data science interviews. Yet, you’d be surprised how often aspiring data scientists invest their learning time on the latest trends and new algorithms but miss the trick by not revisiting basic concepts and get stumped at interviews.

This post will help you better understand the CLT theorem at an intuitive level. It will also help you better appreciate its importance, and the key assumptions when it is used.

Plain English Explanation

In a somewhat formal…


Machine Learning Operations (MLOps) is an emerging field and I strongly encourage you to learn more to catapult your data science career.

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Don’t Let Your Skillset Get Extinct

The data science field is evolving at an unprecedented pace. While the field is certainly in the foreseeable future, your skillset may well do if you cease learning and upskilling.

Data science continues to enjoy the spotlight as more organizations wish to use data to stay competitive. This is promising for each one of us. However, the rising demand also means that an ever-increasing number of people are getting into data science.

With ubiquitous learning opportunities at everyone’s disposal, you must continue to learn and grow to stay competitive in such an environment.

Why is MLOps Important?

This post will introduce…


A case-study-based introduction that will get you started to use the ggplot2 library to create high-quality graphics and learn about the world

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If you have ever wanted to analyze data and add a new toolkit to your skillset that is used by professional data scientists, then read on.

Rather than presenting a dry list of commands, this tutorial will use a specific case study as a motivating example to teach you everything you need to know about ggplot2, the de facto standard for creating high-quality graphics in R. It is a third-party library supported by the ecosystem. While you could plot in R using the base library, you will most likely end up using ggplot2 for any actual project. …


Lesson 2: Being right is not enough, you have to be convincing

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Had the correct scatterplot or data table been constructed, no one would have dared to risk the Challenger in such cold weather. Edward Tufte

It was supposed to be a landmark day in modern history.

The first civilian (a high school teacher named Christina McAuliffe) was selected to go into space. There was even a possibility of a televised conversation between her and President Reagan during the annual State of the Union address, due on the same day in 10 hours. Instead, the space shuttle 73 seconds after launch killing all the seven astronauts on board.

A day before…

Ahmar Shah, PhD (Oxford)

Scientist (several research publications in prestigious journals such as The Lancet, Brain, Thorax, IEEE Transactions), love writing for meaning & impact…

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