Hallo, es ist uns endlich wieder gelungen einen erstklassigen Sprecher für unser Meetup zu gewinnen: Mathias Kirsten, Senior Data Scientist im Bereich Technology & Innovation der Deutschen Telekom AG, wird uns im November zu folgendem Thema aufschlauen (in Englisch):
Automated Machine Learning has become a hot topic in the past two years. Players like DataRobot, H2O or SparkBeyond are pushing the topic onto the Data Science agenda and Company Managers are buying into the marketing message of “Democratizing AI”: Conjuring up expectations to substitute missing Data Scientists by giving data savvy business experts access to such tools. The latter one being a claim that we have heard of again and again with every new generation of Visual Data Analytics platforms since their first appearance in the late 1990s.
Time for a reality check!
In this session, I am going to show and discuss results we obtained at Deutsche Telekom by employing one of the currently most sophisticated Auto Machine Learning tools available on-premise. Benchmarking the tool on several application domains against human Data Scientists as well as other Auto ML tools, I am going to put our findings into perspective with the Data Mining life cycle and show where Auto ML tools actually provide substantial support – but also where it falls short of the expectations and high hopes. Finally, I will conclude with an outlook on the role of Data Scientists and the future relevance of Automated Machine Learning.