Introduction
Machine learning is the basis for most artificial intelligence solutions and works by using large amounts of data to train predictive models.
To train a predictive model, you use a machine learning framework to determine a relationship between the features of entities, and the labels you want to predict for them. For example, you might train a model to predict the expected price of a home based on features such as the property size, number of bedrooms, postal code, and so on.
Azure Databricks provides an Apache Spark based data processing platform that supports multiple popular machine learning frameworks; including Scikit-Learn, PyTorch, TensorFlow, and others. This module uses the Spark MLlib machine learning framework to show examples, but the principles it describes apply to all machine learning frameworks.