{"id":672,"date":"2020-08-24T19:00:10","date_gmt":"2020-08-24T19:00:10","guid":{"rendered":"https:\/\/data-science.gotoauthority.com\/2020\/08\/24\/predictive-analytics-world-berlin-2020-keynote-sessions-announced\/"},"modified":"2020-08-24T19:00:10","modified_gmt":"2020-08-24T19:00:10","slug":"predictive-analytics-world-berlin-2020-keynote-sessions-announced","status":"publish","type":"post","link":"https:\/\/wealthrevelation.com\/data-science\/2020\/08\/24\/predictive-analytics-world-berlin-2020-keynote-sessions-announced\/","title":{"rendered":"Predictive Analytics World Berlin 2020 \u2013 Keynote Sessions Announced"},"content":{"rendered":"
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The PAW Berlin 2020 Keynote Sessions<\/span><\/p>\n

The agenda of Predictive Analytics World<\/strong><\/span><\/a> Berlin is taking shape. Curious? Take a peek\u00a0at our keynote sessions 2020:<\/p>\n

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Use the code\u00a0KDNUGGETS<\/strong>\u00a0for a\u00a015% discount\u00a0on your Predictive Analytics World ticket.\u00a0<\/span><\/p>\n

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How to Scale Data Function in a Fast-Growing Organization?
Learnings from HRS. – Dr.\u00a0S\u00e9bastien\u00a0Foucaud,\u00a0Chief Data Officer<\/strong><\/span><\/p>\n\n\n\n
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In this talk, S\u00e9bastien\u00a0will use concrete examples of problems faced in setting up a large data function and how they are solving it at HRS, in particular in times like during the COVID-19 crisis. The audience will be given the following key takeaways: How to set up your data function for it to scale as fast as your company grows? How can you support your team leads and teams with data in this critical period of growth? What are the best current practices?<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n


How AI Is (Not) Changing Forecasting & Demand Planning
–\u00a0Prof. Dr. Sven Crone, Director |\u00a0Lancaster Research Centre for Forecasting<\/strong><\/span><\/span><\/p>\n\n\n\n
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After a brief introduction into AI\/ML in forecasting, we will explore the differences in data between image recognition and demand planning, where the dataset size, structure, and labels are often sparse. Companies are not drowning in data, but rather sitting in a puddle! As this limits AI\/ML algorithms, we present a case study at one of the world’s leading pharmaceutical manufacturers Janssen (a Johnson & Johnson company) where enhanced datasets with increased sample frequency and automatic feature generation promise break-through increases in accuracy by using AI\/ML.<\/p>\n<\/td>\n

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Coronavirus Update<\/strong><\/p>\n

Hopefully the new normal will allow Predictive Analytics World to take place on-site in Berlin. Should this not be the case it will take place virtually, via live-streaming.\u00a0<\/strong>Safety always comes first!<\/strong><\/p>\n

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Become a\u00a0sponsor<\/strong><\/span>\u00a0and interact with data scientists from around the world or get on board as a\u00a0media partner<\/strong><\/span>,\u00a0share\u00a0the latest news, and earn your complimentary tickets! \u00a0\u00a0<\/p>\n

Get on board<\/strong><\/span><\/a><\/p>\n

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