In this demo, we will go over the various capabilities available in DSS. Specifically, we will look at how to:
- Access data from disparate sources
- Wrangle and prepare data for your specific purposes
- Build and iterate on machine learning models inside DSS
- Visualize results, deploy your models in batch or via API, and operationalize your work
- Export your projects to visualization tools such as Tableau and webapps for external student/research presentations
Dataiku
Technical Evangelist and Sales Engineer
Christina Hsiao is a technical evangelist for Dataiku based in the US. In her role, Christina is able to share her passion for applied data science through writing and by speaking with customers, partners, and organizations interested in solving business problems with the powerful combination of people, data, and technology. Prior to joining Dataiku, she spent nearly 10 years at SAS, mainly ...
Christina Hsiao is a technical evangelist for Dataiku based in the US. In her role, Christina is able to share her passion for applied data science through writing and by speaking with customers, partners, and organizations interested in solving business problems with the powerful combination of people, data, and technology. Prior to joining Dataiku, she spent nearly 10 years at SAS, mainly specializing in Natural Language Processing and text analytics. Christina holds a bachelor’s degree in Mechanical Engineering from Stanford University.
Dataiku
Academic Program Specialist, EMEA
Dataiku
Director of Academics
Dataiku
Academic Program Specialist
Dataiku
Academics Program Marketing Coordinator
