What’s the Point? — One of the most fundamental concepts in data science involves the idea of a “prediction” (the word should probably be “inference”). But how does that happen? What’s going on under the covers? What’s THE fundamental concept? To be thorough, the answer is, “it depends,” but to avoid an overly cerebral…

Use y as the starting point for X — good for machine learning — What’s the Problem? When dealing with a dataset with many features, it can be difficult to separately define the features (X) and the target(s) (y). Defining the target(s) is usually straightforward because there is usually one variable in the target (or there are very few). …

It’s a shapeshifter I say! — Basic Confusion (Matrix) When predicting a categorical variable target, an important model metric tool is the confusion matrix, and that tool is aptly named because the confusion matrix can be very confusing (that’s not even why they call it a confusion matrix). However, with a simple tip, you can avoid confusion and let…

A Surprisingly Tricky Bit for Beginners — One of my professional lives is as an adjunct professor teaching undergrad data science. In that capacity, in predictive analytics (which is a basic overview of data science for all intents and purposes), I’ve found a consistent and surprising pattern with students: They struggle to understand the differences between regression…

Even before you get to the math! — Data science is hard, but not because any single concept is especially hard (noting that some are). The hard part is keeping the basics straight because: Synonym soup Obvious subtlety No clear answers A million situations The basics aren’t basic Synonym Soup It’s hard enough to keep the relatively vast number of…

And why they nothing like == and != — For anyone following me, I apologize that’s it’s been a while since I’ve posted, but I’ve been pretty busy teaching four classes, keeping up with my full-time job, and moving across the country. Excuses aside, here’s a little Python tidbit that can be easily lost in the syntax: the difference…

From a Microsoft ML Studio and Visual Studio Code Fan — The Quick I’m going to cut right to the quick of it — while I really like Azure ML Studio combined with (or without) Visual Studio Code for use with Python Jupyter Notebooks, if you just look at the steps to get up and running, Google Colab (Colaboratory) is hands-down the easier…

The Python Programmer’s Perspective — My journey in data science started during my Master’s in Data Science at Bellevue University, where I learned both R and Python. While I’m a pretty serious Python advocate, it’s not exactly the fastest programming language I’ve ever used (nor the slowest). But I’ve been hearing a lot about Julia’s…

Insights from 11+ Years of Habitual Fitness — I grew up an athlete (competitive swimming) and at a very early age felt the bliss of exercise-induced endorphins. But as life progressed, exercise became less of a priority even as my younger self pulled on the strings of my subconsciousness to get back into it. Then working out started…