Machine Learning Pipeline

What is a machine learning pipeline? In the simplest terms, it is another form of data pipeline. Before data is fed into a machine learning algorithm, it is often raw and needs to be processed. And conversely, ML algorithm outputs need processing for real-world applications.  A machine learning pipeline therefore is used to automate the ML workflow both in and out of the ML algorithm.

A seamlessly functioning machine learning pipeline (high data quality, accessibility, and reliability) is necessary to ensure the ML process runs smoothly from ML data in to algorithm out.

Snowflake and Machine Learning

Snowflake's platform provides full elasticity that allows machine learning data pipelines to handle changing data requirements in real time. Snowflake works with a range of data science and ML/AI partners to deliver faster performance, faster pace of innovation, ease of access to the most recent data, and zero duplication.

To learn more about a real-world use case, read how Tensor flow classification data pipelines can be deployed on the cloud with Snowflake to create an end-to-end machine learning solution in under one hour.