Prescriptive Modeling Makes Causal Bets – Whether You Know it or Not!
modeling is the pinnacle of analytics value. It doesn’t focus on what happened, or even what will happen – it ...
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Exploring the Proportional Odds Model for Ordinal Logistic Regression
You can find the full code for this example at the bottom of this post. odds model for ordinal logistic ...
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The Role of Luck in Sports: Can We Measure It?
: When Skill Isn’t Enough You’re watching your team dominate possession, double the number of shots… and still lose. Is ...
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Data Drift Is Not the Actual Problem: Your Monitoring Strategy Is
is an approach to accuracy that devours data, learns patterns, and predicts. However, with the best models, even those predictions ...
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Estimating Product-Level Price Elasticities Using Hierarchical Bayesian
In this article, I will introduce you to hierarchical Bayesian (HB) modelling, a flexible approach to automatically combine the results ...
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What Statistics Can Tell Us About NBA Coaches
as an NBA coach? How long does a typical coach last? And does their coaching background play any part in ...
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How to Learn the Math Needed for Machine Learning
can be a scary topic for people. Many of you want to work in machine learning, but the maths skills ...
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When Predictors Collide: Mastering VIF in Multicollinear Regression
In models, the independent variables must be not or only slightly dependent on each other, i.e. that they are not ...
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Least Squares: Where Convenience Meets Optimality
0. Least Squares is used almost everywhere when it comes to numerical optimization and regression tasks in machine learning. It ...
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One Turn After Another | Towards Data Science
While some games, like rock-paper-scissors, only work if all payers decide on their actions simultaneously, other games, like chess or ...
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