Overview
The sequential model is the basic model of a neural network, that is, it consists of layers of inputs, weights, an activation function, and a set of outputs, which feeds the next input.
Topics
- Creating a Model - the first step is create the model object using the tensor flow library
- Adding Layers - add layers to the model
- Applying to Input - once a model has been created, it can be applied to an input in order to generate an output
- Fitting - model parameters need to be fit to the training data.
- Weights
- Regularizers
- Troubleshooting
- Validation set