Скачать или смотреть (Loss & Risk)- Intro to Machine learning - Beginner friendly

Description:

In this video, we dive deep into one of the most important foundations of Machine Learning — Error and Risk.
You’ll learn not just what they are, but how they connect to evaluating and improving ML models.

Topics covered:

Understanding error in Machine Learning

Loss functions in classification and regression

0–1 loss

L1 (first norm)

L2 (second norm)

Edge loss (for image regression tasks)

What is risk, and why it matters

Exact risk, empirical risk, and expected risk explained

The difference between population and sample in evaluating models


Whether you’re a beginner or revising your ML basics, this video gives you a clear, intuitive understanding of how we measure and compare model performance — both theoretically and practically.