Abstract: In this session we will address the elephant in the room: That is the difficulties that come with deploying and monitoring machine learning models in production. Normally, the Data Science and the IT team need to work closely for each individual project and more often than not, the deployment can be buggy which leads to excess time being spent in previous projects instead of delivering new value. With the Machine Learning Operations (MLOps) solution provided by DataRobot, you will be able to see how your custom models built with the tools of your choice can be deployed easily and managed with just a few clicks.
Who is this for?
Data Scientists and IT people who want to scale the number of ML models they have into production while still having a good night's sleep at the end of the day!
Bio: Theo is a Customer Facing Data Scientist working for DataRobot where he helps customers achieve their AI goals. Previously, he worked as a Lead Data Scientist in a major Telco Company where he spent the majority of his time building machine learning pipelines using Apache Spark. Furthermore, he is currently completing his Ph.D. at the Athens University of Economics and Business. Theo loves discussing AI and is a frequent contributor to the DataRobot community.
