Why you need to fix your Data Science processes?
Thanks to the great advancements over the past few years in the availability of tools, Machine Learning models can be used to support broad range of business scenarios. Although making the model run on individual's laptop is pretty easy, implementing Machine Learning modelling at scale in complex environment can be tricky.
MLOps became a very hot keyword recently. Initially it reffered to the software solution helping to deploy models, however it became clear that the technology can help to make life easier, but the process behind and the way people organise their work is the clue in gaining effectiveness and scalability. In this webinar we will discuss the need of structuring the way we work with models, building blocks and how they can support the process.
About Speaker:
Rafal is tech enthusiast who was always amazed by data and what insight we can get out of it. He started his career in IT over 13 years as tech data warehousing guy, then moved to Project Management and Business Development. Right is involved in Data analytics and Cloud projects as a part of GetInData team.
