Table Discussions: Best Advice Ever
Date:
Thursday, November 16, 2023
Time:
2:35 pm
Room:
Foyer
Summary:
You are surrounded by fellow ML experts and Data Scientists and there is no better place to discuss and share your common problems. Off the record, and in a small group. These are your people – they understand your situation. Often rated the best part of the event, sharing your problems with like-minded professionals is your path to answers, a little empathy, and a stronger professional network. Come prepared with an issue you are facing, a problem you are solving, or a question that needs answering. And then, be ready and willing to help others to overcome their challenges.
Topics for the roundtable discussions:
From Data to Action: How can we achieve actual impact from our data (Philipp Freytag von Loringhoven)
In a world drenched with data, how do we navigate from raw information to real-world impact? In this discussion, we’ll dive into the complex maze of data transformation, exploring how it’s possible to catalyze tangible change from intangible information. Join a dynamic group of experts in analytics and business intelligence as they unlock the secrets behind successful data implementation in today’s challenging business environment.
ChatGPT Code Interpreter: Opportunity or Threat? (Peter Seeberg)
Do you, Data Scientist, use Code Interpreter for data cleaning, data merging, and analysis, including visualizations of your customer’s data? Have you become more productive since, by being handed initial explorational analysis and reducing repetitive tasks? Do you use Code Interpreter only for initial explorational analysis or also for more complex tasks? Do you, Domain Expert, use Code Interpreter for explorational analysis of your data? Have you become less dependent on your Data Scientist
Generative AI = Booster for Data-Driven Marketing & Sales? – How to leverage LLMs in the B2C Marketing Context (Cecilia Floridi)
Are LLMs just a hype or made to stay? How can we leverage the capabilities in the B2C marketing context, to improve the productivity and the value-add for consumers. We are going to have a open table discussion on use cases from practitioners and want to conclude which use cases worked out and why they succeeded or failed. The use cases shall incorporate various domains like data enrichment, text & content tagging, persona generation or the automation of the generation of highly personalized marketing campaigns. The focus should be on both the added value of the use cases and their operationalization.