Closed loop data science from data management to model training, deployment, scoring, and monitoring
Data scientists must be both consumers and producers of information for model adoption in business critical workflows. With Snowflake's Data Cloud and Snowpark as a common data platform, modeling efforts easily reach end users in a way that maximize business value.
Bringing Snowflake and Domino together makes it easier for researchers and data scientists to access the high-quality information and powerful capabilities from Snowflake, while taking advantage of Domino’s open, extensible Enterprise MLOps framework.
Together, they empower data scientists to access, transform, manipulate, and compute data inside any code library they choose to use with Domino's Enterprise MLOps platform.
Meet the speakers
Nikolay Manchev is the Principle Data Scientist for EMEA at Domino Data Lab.
In this role, Nikolay helps clients from a wide range of industries tackle challenging machine learning use-cases and successfully integrate predictive analytics in their domain specific workflows. He holds an MSc in Software Technologies, an MSc in Data Science, and is currently undertaking postgraduate research at King's College London. His area of expertise is Machine Learning and Data Science, and his research interests are in neural networks and computational neurobiology.
Prash Medirattaa is the Partner Sales Engineer - AI & ML at Snowflake
Prash is a customer-centric professional with many years of data science, consulting, and solution selling experience with a Master’s degree in Data Science and Management. In current role at Snowflake, he leads the technical go-to-market (GTM) and product integration strategy for Snowflake's machine learning partners.
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