Lecture 3: Validation & Why Deep?

By Yinggan XU Dibbla In this Lecture, Lee introduces the idea of select best model through validation set performance. Lee also explains how deep NN outperforms fat (wide) NN. Validation set The CORE question we want to figure out is Why I used validation set but still overfit? graph LR id1[model 1 with para space H1] id2[model 2 with para space H2] id3[model 3 with para space H3] id4[Validation Set] id1-->id4 id2-->id4 id3-->id4 id5[Validation-Loss-1=0....

June 28, 2022 · Dibbla

Lecture 1&2: Basics of ML and Why Fail

By Yinggan XU Dibbla The notebook basically is a summary for what is mentioned in Hung-Yi Lee’s ML course 2022. Sometimes people have contradictive ideas like whether PPO is an off-policy algorithm (or my grammar mistakes in the notebook) , but in this notebook, I’m going to make things aligned with Hung-Yi Lee’s idea. Lecture 1 - Intro & Basic Idea of ML The basic idea of ML, according to Lee, is to find a function....

June 27, 2022 · Dibbla