Keras Workflow
Explore the Keras workflow to build deep learning models effectively. Learn how to read and preprocess data, define model architecture, compile with loss and optimizer settings, train the model using backpropagation, evaluate performance, and make predictions on unseen data.
Steps for building a deep learning model
The Keras workflow has the following steps to develop a deep learning model:
1. Read and explore the data
This step requires reading and exploring the given dataset, preprocessing it (if required), and splitting the input features and the output label from the given dataset. These input features ...