How to develop a successful ML product? Part II

We continue our series of presentations on “end-to-end” ML product development. Today we discuss aspects related to understanding and processing of data in order to prepare it for the modeling phase.

We’ve all been there: At the start of a project you’re given a data dump or access to a database. The task is now to develop a model that solves a clearly defined business problem or how do you go from data to meaningful results? The answer is in the today’s presentation by Magnus Axelsson.