Note: the complete collection of Part 2 video timelines is available in a single thread for keyword search.
Part 2: complete collection of video timelines
Lesson 10 video timeline:
00:00:10 Picking an optimizer for Style Transfer (student post on Medium)
Plus other student posts and tips on class project.
00:07:30 Use Excel to understand Deep Learning concepts
00:09:20 ImageNet Processing (continued from Lesson 9)
& Tips to speed up your model (simd & parallel processing)
00:26:45 Adding Preprocessing to Keras ResNet50
00:28:30 Transfer Learning with ResNet in Keras: difficulty #1
00:33:40 Transfer Learning with ResNet in Keras: difficulty #2
00:38:00 Use batches to overcome RAM “Out of Memory”
00:42:00 Final layers to our ResNet model
00:47:00 Nearest Neighbors to look at examples
00:55:00 Fine-Tuning our models and more “Out of Memory” fixes
01:03:00 Find images similar to a word or phrase &
Find images similar to an image !
01:08:15 Homework discussion
01:16:45 How to: multi-input models on large datasets
01:23:15 Generative Adversarial Networks (GAN) in Keras
01:32:00 Multi-Layer-Perceptron (MLP)
01:37:10 Deep Convolutional GAN (DCGAN)
01:40:15 Wasserstein GAN in Pytorch
01:46:30 Introduction to Pytorch
01:55:20 Wasserstein GAN in Pytorch (cont.)
& LSUN dataset
02:05:00 Examples of generated images
02:09:15 Lesson 10 conclusion and assignments for Lesson 11