User:Jnaglak97/sandbox

The Wide and Deep built-in algorithm is used for large-scale classification and regression problems, such as recommender systems, search, and ranking problems. AI Platform uses an implementation based on a TensorFlow Estimator. This type of model combines a linear model that learns and "memorizes" a wide range of rules with a deep neural network that "generalizes" the rules and applies them correctly to similar features in new, unseen data.

Examples and source code of Wide and Deep Learning is available on GitHub.

Overview
This built-in algorithm does preprocessing and training:

Preprocessing: AI Platform processes your mix of categorical and numerical data into an all numerical dataset in order to prepare it for training. Training: Using the dataset and the model parameters you supplied, AI Platform runs training using Tensorflow's Wide and Deep Estimator.