Custom Models, Layers, and Loss Functions with TensorFlow
In this course, you will:
• Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network.
• Build custom loss functions (including the contrastive loss function used in a Siamese network) in order to measure how well a model is doing and help your neural network learn from training data.
• Build off of existing standard layers to create custom layers for your models, customize a network layer with a lambda layer, understand the differences between them, learn what makes up a cus…
Watch on Coursera ↗
(saves to browser)
DeepCamp AI