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…

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. They demand model…

Develop a robust Feature Selection workflow for any supervised problem — Learn how to face one of the biggest challenges of machine learning with the best of Sklearn feature selectors. Introduction Today, it is common for datasets to have hundreds if not thousands of features. On the surface, this might seem like a good thing — more features give more information about…

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? …

Get that model online — Introduction People say that the best thing about Python is the abundance of its open-source libraries. I beg to differ. Having many alternatives for doing a single task might give you a lot of flexibility, but they might just end up creating a giant mess that leaves programmers confused and angry. …

ExcelWriter, factorize, explode, squeeze, T, mask, idxmax, clip, … — “I wish I could do this operation in Pandas….” Well, chances are, you can! Pandas is so vast and deep that it enables you to execute virtually any tabular manipulation you can think of. However, this vastness sometimes comes at a disadvantage. Many elegant, advanced features that solve rare edge…

Learn new packages like never before — 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. …

Get rich in NumPy — 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…

August 8–14 issue — Welcome to the fourth edition of my newsletter — Tricking Data Science. This issue contains another 28 of my LinkedIn posts for the past week. Thanks to everyone for reading the latest issues! Here are links to them👇 28 Subtle Weekly Machine Learning Tricks And Gem Resources, #4 July 24–31 issueibexorigin.medium.com 28 Subtle Weekly Machine Learning Tricks and Gem Resources, #3 July 10–16 issueibexorigin.medium.com