We’ll walk through an example to predict a target variable’s value using categorical variables via a linear regression equation. In this post, you’ll learn how to establish connectivity between a Couchbase cluster and a Jupyter Notebook, then pull data from Couchbase and use it to train a linear regression model for machine learning. Couchbase lets you store and process vast amounts of data (semi-structured and unstructured) at scale and support the kinds of data the world is full of: narrative text (social media posts, etc.), equations and more. Why? The Jupyter Notebook web application lets you create and share documents that contain narrative text, equations and the like for use cases such as data visualization and machine learning. Data scientists love Jupyter Notebooks – and it makes a natural pairing with the Couchbase document database.
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