Enterprise ML Projects Need More Than AutoML
 

Automated Machine Learning – so-called AutoML —  has received considerable attention in recent years and is poised to take enterprise analytics to the next level. Most often, however, automation has been limited to the model-building algorithms themselves, such as hyper-parameter tuning and model ensembles. It appears that Insufficient progress has been made with the most time-consuming parts of the machine learning process: data preparation, model interpretation and model deployment. This talk will describe why attention in these steps has been slow in coming and practical recommendations for automating them.

Automating Building of Predictive Models: Predictive AI + Generative AI
 

With the emergence of Generative AI as a leading-edge and game-changing technology, it’s natural for data scientists to ask the question, “Can generative AI help me?”. In this workshop, the question will be answered including both “pro” and the “con” sides of using Generative AI for predictive modeling – often now labelled as Predictive AI. Examples with well-known datasets will be used to illustrate the concepts, and all prompts and code used in the workshop will be made available to attendees.

This workshop will include a hands-on portion.