| final_projects | ||
| lecture01_02 | ||
| lecture03_06 | ||
| lecture07_11 | ||
| lecture12 | ||
| lecture13_17 | ||
| lecture18_21 | ||
| lecture22 | ||
| lecture23_24 | ||
| lecture25_26 | ||
| lecture27 | ||
| lecture28_31 | ||
| README.md | ||
Purpose
Following along with the playlist created by Vizuara on Youtube (https://www.youtube.com/playlist?list=PLPTV0NXA_ZSj6tNyn_UadmUeU3Q3oR-hu).
The primary objective is to gain a foundational understanding of simple neural networks including forward propagation, activation layers, backward propagation, and gradient descent.
Lecture Contents
Lectures 1-2 use same handout.
Lectures 3-6 use same handout.
Lectures 7-11 use same handout.
Lecture 12 uses same handout.
Lectures 13-17 use same handout.
Lectures 18-21 use same handout.
Lecture 22 uses same handout.
Lectures 23-24 use same handout.
Lectures 25-26 use same handout.
Lecture 27 uses same handout.
Lectures 28-31 use same handout.