Mental Models

Bias vs. Variance: Why Your ML Model Can’t Have It All

Here’s something that frustrated me for years when I was learning machine learning: every time I fixed one problem with my...
mladvocate
7 min read

Training vs. Testing: Why Your Model Needs to Prove Itself on New Data

Does this sound familiar? You’re tutoring a student for an upcoming math test. You help them solve dozens of practice problems...
mladvocate
5 min read

Prediction vs Inference: Different Goals in ML Analysis

Have you ever wondered why some machine learning applications can make accurate recommendations but can’t explain why, while others provide clear...
mladvocate
5 min read

Classification vs Regression: Predicting What vs. How Much

In our previous post, we explored supervised vs. unsupervised learning. Now we’re diving into another fundamental choice you’ll face in every...
mladvocate
5 min read

Supervised vs Unsupervised Learning: The Two Main Ways Machines “Learn”

Remember learning to ride a bike? Some of us had a parent running alongside, holding the seat and shouting guidance: “Pedal...
mladvocate
5 min read