Tips and Tricks
Become a Matplotlib ninja
Actually, there is no such thing as an advanced Matplotlib user. There is only a matter of who spent more time on the documentation and practiced what they read.
So, if your goal is to become an “advanced Matplotlib user,” there are only two obstacles in your way. One —…
Become a NumPy Ninja
Motivation
Every data scientist admires someone. For some, it might be people who create killer data visualizations; for others, it is simply anyone who answers their StackOverflow questions. For me, it was people who used NumPy like a ninja.
I don’t know. I have always thought that the ability to use…
Works 100%!
I think Windows users, including me, have suffered enough. You are probably stumbling on this after trying hours or even days to make this work. …
Dominate the data science stack quickly
Why do this?
Among productivity gurus, there is a term called "flow state." It happens when you concentrate on what you are doing so hard that you go into some type of a trance. You can't keep your fingers away from the keyboard. …
Use Matplotlib like an absolute boss!
I used to have a rule…
When I was a beginner learning data visualization, I used to have a rule — never, ever visit the Matplotlib documentation.
Nothing good ever came out of there. When I was on its pages, my eyes would process English words but, somehow, they were interpreted into my brain like I…
I hated Sklearn…
Motivation
I hated Sklearn. The “first introduction to ML” course I took explained SVMs so badly that I judged the entire library based on that. I abandoned the course and ML for good for a few months after that.
Explain any black-box model to non-technical people
Motivation
Today, you can’t just come up to your boss and say, “Here is my best model. Let’s put it into production and be happy!”. No, it doesn’t work that way now. Companies and businesses are being picky over adopting AI solutions because of their “black box” nature. …
Let’s catch those high-dimensional outliers!
Introduction
We’ve all used those simple techniques — plot a scatterplot or a KDE, and the data points farthest from the group are outliers. Now, tell me — how would you use these methods if you were to find outliers in, say, 100-dimensional datasets? …
Reduce dimensionality and “see” your data
Introduction
No matter how powerful machine learning models are, they can't quite beat the feeling you get during those "Aha!" moments of exploring data through rich visuals. But, there are so many histograms, scatterplots, heatmaps you can create before you say, "this is really getting old."
In those moments, you need…
Use Pandas the way it was intended to…
Introduction
“Great… another article on how to make Pandas n times faster.”
I think I have said that countless times for the past two years I have been using Pandas. The most recent one I saw said, “make Pandas 71,803 times faster”.
But I won’t give you that kind of promise…
