Details
After the summer break, We're happy to have KI labs as our host for this event! A big Thank You from Kaggle Munich as always!
For those new to Kaggle Munich, we are a community of hobbyists and professionals interested in data science, programming and of course solving challenges on kaggle.com
Whether you're new to data science or a hardened veteran, join us for drinks, food and exciting talks!
Talks:
1. “Kaggle Competition: Understanding Clouds from Satellite Images - Introduction from a host” - Stephan Rasp
Summary:
I will present an active Kaggle competition that I am co-organizing. The goal of the competition is to detect four cloud patterns from satellite images. The cloud patterns are called Sugar, Flower, Fish, and Gravel. In the talk, I will explain why climate scientists care about structures and clouds and how we ended up with these silly names. Then I will also delve into the details of what makes this image segmentation challenge a little different.
Bio:
Stephan Rasp is a postdoc at TUM trying to figure out how to improve climate models with ML
2. "ML-Navigator: Open source tutorial-based Machine Learning framework: IEEE-CIS Fraud Detection competition"-Maher Deeb.
Summary:
I have been working on developing an open-source project (ML-Navigator) for more than 2 months. The main goal is to help new Data Science joiners to jump in the Data Science world fast and confidently. I hope that I can make ML-Navigator a great chance for Kaggle Munich community to contribute to the open-source world. Together with the Kaggle Munich community, I hope that we can bring the project ahead to the level that ML-Navigator will be appreciated by the Data community.
https://github.com/KI-labs/ML-Navigator
Bio:
Maher Deeb is a data scientist @ KI labs who builds End-2-End data pipelines.
AGENDA
19:00 - Doors open
19:25 - Welcome from Kaggle Munich and KI labs
19:30 - First talk: “Kaggle Competition: Understanding Clouds from Satellite Images - Introduction from a host” - Stephan Rasp
20:05 - Second talk: "ML-Navigator: Open source tutorial-based Machine Learning framework: IEEE-CIS Fraud Detection competition" Maher Deeb
20:35 Drinks, networking, and hacking
