Director of Customer & Growth Analytics, IAG
In this corollary to Austin Byrne's talk in June, Willem shared his team's journey to escape the typical value-providing drudgery of dashboards, reports, and PowerPoints - and move towards more advanced challenges with more diverse, longer term, business values. Is there a binary choice between elementary reporting and advanced statistical work? How do you harness the curiosity, learning, and skills from the latter to motivate and propel your team towards both? This talk put the spotlight on the passionate individuals and how they can actually make differences for customers and their organisation.
Co-founder & Practice Director, Intellify
Time-series, as a field of study, has largely focused on statistical methods that work well under strict assumptions. Specifically, when there is sufficient history, there is little meta-data and a well-formed auto-correlation structure. However, as an applied practitioner Kale knows that most real-world time series problems violate these assumptions. This leaves us with an opportunity to use more modern time series methods, based on machine learning, to overcome these deficiencies.
This session spoke about the unique properties of time-series, how statistical methods work and how and why machine learning (and deep learning) methods can be used to improve accuracy.