Deepak Mehta·Oct 25Broad Categories of Machine-Learning Models: Supervised Learning Models — Part eArticle 2e of 25 — Regression Model Families
Iuri de Araujo·Sep 6From GL to Gradient Boosting: Building a Churn Model on Top of a Governed Finance Metrics LayerHow a dbt semantic layer becomes the training set for an ML model — and why that ordering matters more than the algorithm you pick
Feiza Data·Sep 1Symbolic Regression: A Math-First Approach to ExtrapolationWhile scrolling through LinkedIn a few weeks back, I stumbled across a post on a data model I’d never heard of before. Many traditional…
Carlos Ebratt·Apr 20Regression Analysis: Simplify Complex Data Relationships with Python.We all know that in the data science space, there are problems we face as professionals when managing to turn a hidden problem in data into…
Teja Loya·Sep 16, 2025How would you deal with multicollinearity in regression models?In regression analysis, multicollinearity happens when two or more independent (predictor) variables are highly correlated. This can…
Sukant Ranjan·Aug 9, 2025Tobit vs Beta regression modelsA brief introduction and comparison between them
Moustafa Mohamed·Jul 8, 2025A Comprehensive Guide to Supervised Learning Models in Machine LearningA Comprehensive Guide to Supervised Learning Models in Machine Learning
Fahmi abdul aziz·Jun 16, 2025Creating sample regression dataWe’ve already discussed some of the basic principles of regression modeling using TensorFlow, especially what a regression problem is. Now…
Matthew·Jun 16, 2025How would you deal with multicollinearity in a regression model?Dealing with multicollinearity — when two or more predictors in a regression model are highly correlated — is important because it:
WonHee Lee·Jun 7, 2025“Predictive Power Unleashed: Building Robust Regression Models with Smart Prompt Engineering”🤖Do you believe that your regression models are truly reaching their full potential?
