Classify structured data with feature columns
Classify structured data with feature columns Run in Google Colab View source on GitHub Download notebook This tutorial demonstrates how to classify structured data (e.g. tabular data in a CSV). We will use Keras to define the model, and feature columns as a bridge to map from columns in a CSV to features used to train the model. This tutorial contains complete code to: Load a CSV file using Pandas . Build an input pipeline to batch and shuffle the rows using tf.data . Map from columns in the CSV to features used to train the model using feature columns. Build, train, and evaluate a model using Keras. The Dataset We will use a small dataset provided by the Cleveland Clinic Foundation for Heart Disease. There are several hundred rows in the CSV. Each row describes a patient, and each column describes an attribute. We will use this information to predict whether a patient has heart disease, which in this dataset is a binary classification task. Following is a description of thi