Browsing: Regression

on linear regression, we solved a linear regression problem using the concept of vectors and projections instead of calculus. Now in this blog, we once again…

to evidential deep learning (EDL), a framework for one-shot quantification of epistemic and aleatoric uncertainty. More specifically, we will focus on a subset: deep evidential regression…

people! If you have ever wanted to understand how linear regression works or just refresh the main ideas without jumping between lots of different sources –…

think that linear regression is about fitting a line to data. But mathematically, that’s not what it’s doing. It is finding the closest possible vector to…

learns machine learning usually starts with linear regression, not just because it’s simple, but because it introduces us to the key concepts that we use in…

At first glance, adding more features to a model seems like an obvious way to improve performance. If a model can learn from more information, it…

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We…

In my previous article I explained how YOLOv1 works and how to construct the architecture from scratch with PyTorch. In today’s article, I am going to…

, we ensemble learning with voting, bagging and Random Forest. Voting itself is only an aggregation mechanism. It does not create diversity, but combines predictions from…

With Logistic Regression, we learned how to classify into two classes. Now, what happens if there are more than two classes. n is simply the multiclass…