08:30
|
Doors Open
|
|
time |
Kuppelsaal |
B09 |
B07-B08 |
B05-B06 |
A1 |
A03-A04 |
A05-A06 |
C04 Open Space (at bcc only) |
|
Toxic Code & People
|
Speed / AI in Enterprise
|
Code Quality
|
Streamlit in Practice
|
NLP / Sci-Kit
|
Tutorial @ 9:00
|
|
09:00
|
Biases in Language Models
sonam
09:00-09:30
|
Speeding up Python with Zig
Adam Serafini
09:00-09:30
|
Secure ML: Automated Security Best Practices in Machine Learning
Alejandro Saucedo
09:00-09:30
|
How a simple streamlit dashboard will help to put your machine learning model in production
Daniël Willemsen, Welmoet Verbaan
09:00-09:30
|
deepdoctection - An open source package for document intelligence
Janis Meyer
09:00-09:30
|
Faster Workflow with Testdriven Development
Torsten Zielke
9:00-10:30
|
Data Science at Scale with Dask
Richard Pelgrim
09:00-10:30
|
|
09:40
|
How to deal with toxic people
Gina Häußge
09:40-10:05
|
Unsupervised shallow learning for fraud detection on marketplaces
Andreu Mora
09:40-10:25
|
conda-forge: supporting the growth of the volunteer-driven, community-based packaging project
Wolf Vollprecht, Jannis Leidel, Jaime Rodríguez-Guerra
09:40-10:25
|
Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit
Antoine Toubhans
09:40-10:25
|
`python-m5p` - M5 Prime regression trees in python, compliant with scikit-learn
Sylvain Marié
09:40-09:55
|
|
10:20
|
Coffee Break
|
|
time |
Kuppelsaal |
B09 |
B07-B08 |
B05-B06 |
A1 |
A03-A04 |
A05-A06 |
C04 Open Space (at bcc only) |
|
AI in Enterprise
|
Database & FastAPI
|
Code Quality
|
Prediction
|
Visualisation
|
Tutorial @10:45
|
|
10:50
|
5 Things You Want to Know About AI Adoption in the Enterprise
Alexander CS Hendorf
10:50-11:20
|
Using a database in a data science project - Lessons learned in production
Jacopo Farina
10:50-11:20
|
Unclear Code Hurts
Dario Cannone
10:50-11:20
|
Predictive Maintenance and Anomaly Detection for Wind Energy
Tobias Hoinka
10:50-11:20
|
Your data, your insights: creating personal data projects to (re-)own the data you share
Paula Gonzalez Avalos
10:50-11:20
|
ML Communication 101: How to talk about Machine Learning with anyone
Julia Ostheimer
10:45-12:15
|
We know what your app did last summer. Do you? Observing Python applications using Prometheus.
Jessica Greene (she/her), Vanessa Aguilar
10:50-12:20
|
|
11:30
|
Do we really need Data Scientists?
Dr. Setareh Sadjadi
11:30-12:00
|
5 Things we've learned building large APIs with FastAPI
Maarten Huijsmans
11:30-12:15
|
A data scientist's guide to code reviews
Alexandra Wörner
11:30-12:00
|
Making Machine Learning Applications Fast and Simple with ONNX
Jan-Benedikt Jagusch, Christian Bourjau
11:30-12:15
|
Sankey Plots with Python
Daniel Ringler
11:30-12:00
|
|
12:00
|
Lunch
|
Reserved for PyLadies
|
time |
Kuppelsaal |
B09 |
B07-B08 |
B05-B06 |
A1 |
A03-A04 |
A05-A06 |
C04 Open Space (at bcc only) |
|
Model Drift & Labeling
|
Web
|
PyData Testing
|
Jupyter
|
DevOps
|
Tutorial @ 13:00
|
|
13:10
|
Detecting drift: how to evaluate and explore data drift in machine learning systems
Emeli Dral
13:10-13:40
|
Forget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.
Dom Weldon
13:10-13:40
|
What are data unit tests and why we need them
Theodore Meynard
13:10-13:40
|
Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team
Alena Guzharina
13:10-13:40
|
Battle of Pipelines - who will win python orchestration in 2022?
Jannis Grönberg
13:10-13:40
|
Aspect-oriented Programming - Diving deep into Decorators
Mike Müller
13:00-14:30
|
Reproducible machine learning and science with python
Prabhant Singh
13:10-14:40
|
Reserved for PyLadies
|
13:50
|
Efficient data labelling with weak supervision
Maria Mestre
13:50-14:20
|
But this is an OAuth, is it not?
Sara Jakša
13:50-14:20
|
Machine Learning Testing Ecosystem of Python
Yunus Emrah Bulut
13:50-14:35
|
JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Jeremy Tuloup
13:50-14:25
|
The state of DevOps for Python projects
Tobias Heintz
13:50-14:20
|
|
14:20
|
Coffee Break
|
|
time |
Kuppelsaal |
B09 |
B07-B08 |
B05-B06 |
A1 |
A03-A04 |
A05-A06 |
C04 Open Space (at bcc only) |
|
PyLadies
|
Python
|
Web / Django
|
Prediction
|
Computer Vision
|
Tutorial @ 14:45
|
|
14:50
|
Python for Everyone - PyLadies' Insights Panel Discussion
Jessica Greene (she/her)
14:50-15:50
|
Stupid Things I've Done With Python
Mark Smith
14:50-15:20
|
Web based live visualisation of sensor data
Jannis Lübbe
14:50-15:20
|
Honey, I shrunk the target variable! Common pitfalls when transforming the target variable and how to exploit transformations.
Florian Wilhelm
14:50-15:20
|
Challenge Accepted - How to Escape the Quicksand While Engineering a Computer Vision Application
Bettina Heinlein
14:50-15:15
|
Introduction to MLOps with MLflow
Tobias Sterbak
14:45-16:15
|
Easily build interactive plots and apps with hvPlot
Philipp Rudiger, Maxime Liquet
14:50-16:20
|
|
15:30
|
Slack bots 101: An introduction into slack bot-based workflow automation
Jordi Smit
15:30-16:00
|
Make the most of Django
Paolo Melchiorre
15:30-16:00
|
My forecast is better than yours! What does that even mean?
Illia Babounikau
15:30-16:00
|
Grokking LIME: How can we explain why an image classifier "knows" what’s in a photo without looking inside the model?
Kilian Kluge
15:30-16:00
|
|
15:50
|
Coffee Break
|
|
16:20
|
Announcements
|
|
16:30
|
5 Years, 10 Sprints, A scikit-learn Open Source Journey
Reshama Shaikh
16:30-17:15
|
|
17:15
|
Lightning Talks
|
|
18:30
|
bcc closed
|
|
19:00
|
Social Event
|
|