Table of Contents
0:00 Intro
0:31 Goal of this lecture
2:08 What is deep learning?
7:06 Why deep learning now?
9:33 Deep learning pipeline
12:17 General overview
16:02 Organization of the course
18:24 A first example in Colab (setting)
19:35 Dogs vs cats (data wrangling)
25:50 Data processing (dataset and dataloader)
40:51 VGG model
45:55 Modifying the last layer
49:50 Choosing your loss and optimizer for training
57:40 Precomputing features
1:03:39 Qualitative analysis
⚠ Dogs and Cats with VGG: static notebook, code (GitHub) or running in colab GPU is required for this notebook ⚠
⚠ More dogs and cats with VGG and resnet in colab GPU is required for this notebook ⚠
Last modified: July 11, 2024. Website built with Franklin.jl and the Julia programming language. 
