Day 51 of 100 Days of AI

I’m about 60% through this workbook, and I have to admit, I really I’m skipping most of the more mathsy bits. I read the Ridge (L2) and Lasso (L1) Regularization sections today and though I didn’t follow the maths fully, at least I came away with the appreciation of a key idea.

To prevent machine learning models from being overtrained (or rather, “overfitted”) to the training data, it helps to increase the bias of the models somewhat by using a variety of techniques. These include Ridge and Lasso Regularization.

If I was doing ML professionally I’d have to nail these concepts. Thankfully, I’m a hobbyist and I’m more interested in the applied components of the field than the depth of all the underlying maths.