# Lesson 2 Timeline

From Deep Learning Course Wiki

- 0:09 - Teaching Approach
- 17:14 - Solution to Dogs vs Cats Redux Competition
- 17:30 - Downloading the Data
- 20:00 - Planning (Overview of Tasks)
- 20:25 - Preparing the Data (Validation and Training Set)
- 22:15 - Using Vgg16 (Finetune and Train)
- 22:48 - Submitting to Kaggle
- 30:30 - Competition Evaluation Metric: Log Loss
- 37:18 - Experiment: Running More Epochs
- 40:37 - Visualizing Results

- 47:37 - Introducing the Kaggle State Farm Competition
- 50:29 - Question: Will ImageNet Finetuning Approach work for CT Scans?

- 53:10 - Lesson 0 Video, Convolutions
- 54:09 - Why do we do finetuning?
- 54:43 - What do CNNs learn?
- 1:03:30 - Deep Neural Network in Excel
- 1:07:54 - Initialization

- 1:14:08 Linear Model from Scratch
- 1:25:37 Linear Model in Keras
- 1:29:58 Linear Model with CNN Features for Dogs Vs Cats Redux
- 1:44:12 Introducing Activation Functions
- 1:46:51 Universal Approximation Theorem
- 1:48:20 Review: Vgg16 Finetuning