Autoplay Next video from Max length

Extending Spark Machine Learning: Adding Your Own Algorithms and Tools

4,095 views · Published 12 June 2017 · 31:03 · Indexed 8 November 2026

Channel: Databricks · 2017 · Science & Technology

Apache Spark's machine learning (ML) pipelines provide a lot of power, but sometimes the tools you need for your specific problem aren't available yet. This talk introduces Spark's ML pipelines, and then looks at how to extend them with your own custom algorithms. By integrating your own data preparation and machine learning tools into Spark's ML pipelines, you will be able to take advantage of useful meta-algorithms, like parameter searching and pipeline persistence (with a bit more work, of course). With Holden Karau and Seth Hendrickson

About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
Read more here: https://databricks.com/product/unified-data-analytics-platform

Connect with us:
Website: https://databricks.com
Facebook: https://www.facebook.com/databricksinc
Twitter: https://twitter.com/databricks
LinkedIn: https://www.linkedin.com/company/databricks
Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader-by-gartner

Extending Spark Machine Learning: Adding Your Own Algorithms and Tools

More from this channel