- Functional APIs
- Compare how the Functional API differs from the Sequential API, and see how the Functional API gives you additional flexibility in designing models. Practice using the functional API and build a Siamese network!
- Custom Loss Functions
- Loss functions help measure how well a model is doing, and are used to help a neural network learn from the training data. Learn how to build custom loss functions, including the contrastive loss function that is used in a Siamese network.
- Custom Layers
- Custom layers give you the flexibility to implement models that use non-standard layers. Practice building off of existing standard layers to create custom layers for your models.
- Custom Models
- You can build off of existing models to add custom functionality. This week, extend the TensorFlow Model Class to build a ResNet model!
- Bonus Content - Callbacks
- Custom callbacks allow you to customize what your model outputs or how it behaves during training. This week, implement a custom callback to stop training once the callback detects overfitting.
