Databricks for Data Science: Experimentation to Productionization
Every day organizations around the world are rapidly accumulating and exploring their data, looking to put it to use. Databricks, and its multitude of features, enables companies to progress from initial experimentation to full-on production-level data science and analytics in one complete platform.
Databricks for Data Science: Experimentation to Productionization (25 mins)
It’s challenging enough to successfully define and run an experiment. The productionization and deployment of it shouldn’t add to those challenges. With Databricks, we can much more easily manage the entirety of the ML lifecycle from experimentation to deployment in one place.
In this recorded webinar, Thorogood Data and Analytics Consultants Deepika Bhatt and Brendan Lundquist speak about Databricks and the exciting ways it can help you and your organizations continue to advance their advanced analytical capabilities.
What we cover:
- How Databricks can unite data analysis, data engineering, and data science in one cohesive platform and how it fits with a modern, data-driven organization.
- An overview of Databricks and key product offerings helping to accelerate productionization, like MLFlow, AutoML, Delta, Feature Stores, and more.
Is it for you?
- Are you looking to understand how Databricks can help you in bringing an experiment to production?
- Are you an individual seeking tooling that can help your data scientists and data engineers work more effectively together?