Machine Learning Workflows at Scale: Challenges and Solutions (Part 1)
Building end-to-end machine learning workflow is very crucial for enterprises to realize full potential from their AI & ML investment. However, it is one of the most challenging part especially when coupled with the problem of scale. In this session, you will learn about the challenges and potential solutions for building and maintaining large scale machine learning workflows for enterprises? You will also learn about common architectural patterns and best practices while designing AI & ML based products or services.
Abhishek Kumar is a Senior Manager of Data Science at Publicis Sapient, where he is focused on applying methods in machine learning to opportunities in retail, ecommerce, marketing and operational optimization. He is completed his MIDS degree at the School of Informtion in 2016.