Please note:
On this site, there is only displayed the English speaking sessions of the TDWI München digital. You can find all conference sessions, including the German speaking ones, here.
The times given in the conference program of TDWI München digital correspond to Central European Time (CET).
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ROOM K4 | Explainable AI - Why interpret-able models are good models
Machine learning and AI have changed the world of data processing and automation at a breathtaking pace, at the cost of turning algorithms into hard-to-control and monitor black boxes.
We present methods and concepts of explainable AI that aim to open the black box and tame these algorithms.
Target Audience: Decision-Makers/Stake Holders in AI & model development, Data Scientists
Prerequisites: general awareness of modeling pipeline and challenges, no coding/math skill required
Level: Basic
Maximilian Nowottnick is a Data Scientist at the full-service data science provider Supper & Supper GmbH from Germany. He has a B.Sc. and a M.Sc. in Physics and extensive knowledge in developing AI solutions in the areas of GeoAI and Mechanical Engineering. He was one of the driving engineers to develop the first SaaS solution of Supper & Supper, called Pointly for 3D point cloud classification.
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ROOM K4 | Harness the power of language with NLP in the Cloud
Natural Language Processing (NLP) allows us to deeply understand and derive insights from language, ultimately leading to more automated processes, lower costs, and data-driven business decisions.
Google is recognized as a market leader in AI and has built a range of solutions incorporating NLP to address a myriad of business challenges. This talk will introduce a few possible solutions, as well as some business use cases on how to incorporate them in a variety of industries.
Target Audience: Middle and upper-level management, Business users with AI/machine learning challenges, BI/Data professionals
Prerequisites: Basic knowledge of machine learning and cloud technology, interest in NLP
Level: Intermediate
Catherine King is a Customer Engineer at Google Cloud and is a Google Cloud Certified Professional Data Engineer. She works with customers in the Public Sector and supports them in digital transformations, big data analytics, and artificial intelligence implementations. Before Google, she worked for many years in the Translation Industry designing Machine Translation models for enterprise clients.
Catherine holds an MSc in Data Science and is passionate about decision science and data-driven cultures.
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