How to Automate Machine Learning and Scale Delivery

Presented by

Nauman Fakhar, Solutions Architect at Databricks Brett Olmstead, Data Scientist at DataRobot

About this talk

On-Demand Webinar Creating and testing machine learning models is time consuming, and delivering results in production at high volumes is prone to error. Automating the development of models is not only helping companies reduce errors but it’s also uncovering powerful business insights - faster. Join our upcoming webinar, How to Automate Machine Learning and Scale Delivery, to learn how to: Use automation to dynamically select optimal machine learning models for your use case Automate the process of deploying models to production with high-volume data pipelines Configure your automation to quickly scale up and down as data volumes change

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Databricks’ mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the team who created Apache Spark™, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership.