About the talk: Automated ML is a game changer for Data Scientists who can now focus on features enginnering and model interpretation. How does it work in a citizen way or with the Python SDK automl.core ? What are the beneficits of this approach ? Which are the common mistakes with the User Interface and all the possibilities with the code ? Is it a too much "closed box" way ? No, because we now have time to interpret ! About Paul: Passionate about statistics since my studies, I followed the rise of Big Data with a lot of interest and the progress of Artificial Intelligence (Machine Learning, NLP ...) open unlimited perspectives. I have been working in the consulting field for almost 15 years, with the desire to understand the expectations of the trades and to help through numerous trainings. Understanding the issues around data and its uses is fundamental. Ethical aspects are also essential to take into account.
Senior Consultant Data & AI @ AZEO - Microsoft AI & Data Platform MVP
Microsoft AI MVP