«Time Series Forecasting»
By the scikit-learn core developers Olivier Grisel and Guillaume Lemaitre.

For experienced data scientists and ML Engineers - limited to 20 participants

This hands-on workshop will use both real world production and environmental data to illustrate how to deal with common data-quality problems. We will also use some specially crafted synthetic data to emphasize catastrophic pitfalls related to edge cases to gain deeper insights about our modeling choices and their limitations..

«When should you use Survival analysis and competing risk modeling using HAZARDOUS?»
by Vincent Maladière, AI/ML Research Engineer.

For all Data Science and Machine Learning Practitioners

One-hour thematic conversations on data science and engineering topics. An expert speaker presents a problem / topic and his vision of best practices, methodology, tools, etc. for 20 to 30 minutes. The rest of the session is devoted to questions and discussions around the presentation. A knowledge sharing & networking space. All conversations are in English.

 
for data science at scale

We built Skore hub as the missing layer between your team's experimentation and production environments. It extends our open-source skore library (the scikit-learn side kick) to bring structure to your development workflow before heavy MLOps tooling becomes necessary.

ML Challenge using skore

For all Data Science and Machine Learning Practitioners.

A team-building experience centered around a stimulating challenge. For our part, this will be an opportunity to see how skore works in real-life conditions: we'll add a few constraints along the way!

- Location: at Probabl, in the Montparnasse Tower in Paris
- Date: Tuesday, April 29th, all day
- Lunch: provided by probabl
- Task: A time series regression. 
- Team size: 2 to 4 people

«Best practices to open source a product and creating a community around it»
by Adrin Jalali, VP Labs & core developer of scikit-learn.

Designed for a general audience – no prior knowledge required.

One-hour thematic conversations on data science and engineering topics. An expert speaker presents a problem / topic and his vision of best practices, methodology, tools, etc. for 20 to 30 minutes. The rest of the session is devoted to questions and discussions around the presentation. A knowledge sharing & networking space. All conversations are in English.

«Aligning probabilistic classification with business decisions using scikit-learn»
By the scikit-learn core developers Olivier Grisel and Guillaume Lemaitre.

For experienced data scientists and ML Engineers - limited to 20 participants

A hands-on, business-centric training experience based on real industry case studies. A great opportunity to enhance your data strategy skills while connecting with industry leaders during the networking cocktail