Logistic Regression From Scratch With Python
Logistic regression is the simplest classification algorithm you’ll ever encounter. It’s similar to the linear regression explored last week, but with a twist. More on that in a bit. Today you’ll get your hands dirty by implementing and tweaking the logistic regression algorithm from scratch. This... Read more
Solving for Unobserved Data in a Regression Model Using a Simple Data Adjustment
Article originally posted here by Doordash. Making accurate predictions when historical information isn’t fully observable is a central problem in delivery logistics. At DoorDash, we face this problem in the matching between delivery drivers on our platform, who we call Dashers, and orders in real-time. The... Read more
Modeling Regression Trees
Decision Trees (DTs) are probably one of the most popular Machine Learning algorithms. In my post “The Complete Guide to Decision Trees”, I describe DTs in detail: their real-life applications, different DT types and algorithms, and their pros and cons. I’ve detailed how to program Classification Trees,... Read more
A Survey of Popular Ensemble Methods – Part 1
This article is the first in a four-part series that introduces three popular ensemble methods: bagging, boosting, and stacking. This post threads the concepts and intuition of all three, while the subsequent three posts are a comprehensive dive into each method that will include runnable R... Read more
Using the NGBoost Algorithm
This post discusses using the NGBoost algorithm. Data scientists competing in Kaggle competitions often come up with winning solutions using ensembles of advanced machine learning algorithms. One particular model that is typically part of such ensembles is Gradient Boosting Machines (GBMs). Gradient boosting is a machine... Read more
3 Regression Pitfalls in Business Applications
Regression is a fantastic tool for aiding business decisions. The traditional purpose of a regression model is to find the mean value of a dependent variable given a set of independent variables. In a business, this purpose should be expanded to include the reduction of uncertainty... Read more
Regression Blog 2: We’re Practically Giving These Regressions Away
When I heard that they would be releasing Pumpkin Spice Spam, I thought of regression. This might seem like a leap, but bear with me. In the U.S. in the last few years, hearing news reports of unusual Pumpkin Spice flavored products means the unofficial end of... Read more