Munich Datageeks May Edition

We are incredibly happy to announce our next Meetup on May 23th at b.telligent!

Format:

• 2 talks (each ca. 40 min incl. discussion)
• Time for networking + food + drinks before, in between and after the presentations
• Talks are held in English
• We will be taking photos and/or film footage at the event. These will be used to share news about our meetups, and to publicize upcoming events.

The lineup:
Heidi Seibold - Are (data) scientists bad at science?

Abstract:
Let's face the facts: most research is not reproducible. That means, if you run the same analysis on the same data of a (data) science project again, you will likely not receive the same results. Ups! In this talk I want to explore the stumbling blocks that (data) scientist run into and what to do about it. Spoiler: it has a lot to do with getting organized.

Bio:
Heidi is a trainer and consultant for open and reproducible data science. Since leaving her own academic career she supports researchers in improving the way they do research through open science and reproducible research practices. Heidi publishes a weekly newsletter (https://heidiseibold.ck.page) and hosts two podcasts (https://heidiseibold.com/podcasts/).

Second talk:
Yannick Franke - How machines watch movies and what people think about them

Abstract:
Movies are a special kind of data. Moving images and language meet. A movie contains a lot of information, but it is very compressed in the producer's description.
For different use cases, however, a deeper scene-level information level may be necessary. In an exploratory project, we investigated how meta-data can be extracted directly from the footage using techniques such as computer vision and NLP. For this purpose, a multi-stage procedure was developed to first cuts films into scenes and then analyze the scene content.
A semantic search is used to check the plausibility of the results and thus clarify the points at which AI and humans understand the same thing but mean something different. Limits and possibilities are shown and further development opportunities are highlighted.

Bio:
Yannick Franke is Senior Data Scientist and Team Lead at b.telligent. After his studies in Economics and Data Science, he has been working as a Data Scientist for over 5 years now with a focus on Computer Vision. He has implemented various projects in the e-commerce, media and industry sectors, primarily using GCP.