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❄️ DSF WinterFest 2025: Global Online Summit ❄️

Join the global data celebration!

Monday 24th to Friday 28th November 2025 Online \| 2-3 sessions per day \| Theme: Innovating with Data

DSF WinterFest is back, and this year, it’s going global! Join our 50,000-strong community for a week of world-class talks, tutorials, and panels exploring how data, AI, and analytics are reshaping the world. Expect inspiring content, expert insights, and the cosy, welcoming DSF atmosphere we are known for, all from the comfort of your own space!

Why join? 🌍 A global stage with speakers and attendees from every corner of the world 🎟️ One ticket for the full week. Register once and access every session 💻 Easy access from anywhere. Join live or catch replays in your own time ☕ Cosy community vibe. No travel, no stress, just data and connection

➡️ REGISTER HERE FOR FREE! ⬅️

🎟️ Tickets:

Choose your experience and secure your spot today: Free Pass - Watch live and enjoy replays until 30 November 2025 Upgrade at Checkout - Get extended replay access until May 2026

Register on our website to receive your joining links, add sessions to your calendar, and tune in live from anywhere in the world.

Please note: Clicking “Attend” on Meetup does not register you for this summit. You must register via our website to receive your links.

🎁 Competition:

We’re spreading festive cheer! One lucky attendee will win a £300 Amazon gift voucher (or equivalent in your currency). Find out more here.

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Session details:

💡 Competitor Response Planning Suite - Turning Threats into Strategic Advantage 🗓️ Wednesday 26th November ⏰ 12:30 PM (GMT) 🗣️ Rajat Kumar, Applied Data Science Manager @ dunnhumby and Namish Kaushik, Senior Applied Data Scientist @ dunnhumby

In today’s hyper-competitive retail environment, the presence of a competitor store isn’t just a challenge - it’s a direct threat to customer loyalty, sales, and profitability. This session introduces the Competitor Response Planning (CRP) Suite, a pioneering solution that fuses geo-spatial intelligence with predictive modeling to help retailers proactively counter competitive impact.

Built on the theme of “Innovating with Data”, the CRP Suite is a three-pronged modeling framework designed to predict customer churn risk across New Competitor Advent, Existing Competitor Landscapes and Instore Media Optimization.

The session will showcase how the CRP Suite integrates retailer data with third-party sources to extract key variables—store DNA, customer behavior, and geo-location—and trains custom propensity models tailored to different competitor types. This enables targeted retention strategies that replace generic mass offers with personalized interventions.

Attendees will also explore how the CRP Suite has been productionized into the Voila dashboard, empowering non-technical users to self-serve insights, trigger models, and navigate competitive threats with ease. Whether you're a data scientist, marketer, or business strategist, this session will demonstrate how data innovation can transform competitive threats into strategic opportunities—driving measurable outcomes for retailers and delighting customers through personalization.

➡️ REGISTER HERE FOR FREE! ⬅️

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🔗 How to join:

Once registered, you’ll receive your unique joining link by email, plus handy reminders one week, one day, and one hour before each session. Don't forget to add the sessions you are attending to your calendar. If you can’t make it live, don’t worry, your ticket includes replay access until 30 November 2025 (or May 2026 with the upgrade).

📘 Reminders:

Time zones: All sessions are listed in GMT - please check your local time when registering.

Recordings: Access replays until 30 November 2025 with a free pass, or until May 2026 with an upgraded ticket

Please note: Clicking “Attend” on Meetup does not register you for this summit. You must register via our website to receive your links.

➡️ REGISTER HERE FOR FREE! ⬅️

Join the Celebration ❄️ Five days. Global speakers. Cutting-edge insights. Free to join live - replays included. Upgrade for extended access. Register now and be part of the global data community shaping the future. #DSFWinterFest

Executive roundtable discussion on how platforms act as the foundation layer for AI initiatives. Topics include the implications of the latest DORA report and State of AI in Platform Engineering, the AI–platform engineering relationship, and lessons from top-performing organizations on unlocking real value from AI initiatives using platforms.

========== INSCRIPTION ==========

https://www.linkedin.com/events/enterthedaggerverse7341139672217145346/ (Le live se déroule sur Linkedin)

========== RECAP' LIVE ==========

Date : mardi 24.06.2025 Heures : 12h00 > 13h00

========== DESCRIPTION ==========

Si je vous dis Dagger ? Cela ne vous parle peut être pas. Si je vous dis... Docker ? Là, ça vous parle !

Dagger, c'est le moteur de CI/CD développé par Solomon Hykes, le papa de Docker. Un OVNI dans l'univers des moteurs de CI/CD, à la fois une alternative et un complément à Jenkins, Circle, GitHub Actions. Mais quid du Daggerverse ?

Laissez nous vous embarquer dans ce nouvel univers, laissez nous vous faire tomber dans... le Daggerverse of madness !!

Dans ce talk, vous :

• prendrez en main Dagger avec le langage de votre choix : Typescript, Go ou Python (et qui sait, Java ?)
• découvrirez comment publiez votre propre module Dagger dans... le Daggerverse !

Vous découvrirez même comment en évitant le push and pray, vous augmentez votre productivité, votre satisfaction et réduisez votre impact énergétique.

Et vous serez à tout jamais séduit par Dagger et son univers à part entière.

========== SPEAKERS ==========

Emeric Martineau - Ingénieur DevOps @ Crédit Agricole Technologies et Services Julien Haumont - SRE @ BlaBlaCar

Join PyData Boston for a night of in-person networking and expert speakers!

6:30-7:00 - Networking 7:00-7:45 - Featured speaker - Eric Ma: What makes an agent? 7:45-8:15 - Break + Networking 8:15-9:00 - Discussion group - LLM applications 9:00-9:30 - Wrap up 🏠 Venue provided by Moderna

This, and all NumFOCUS-affiliated events and spaces, both in-person and online are governed by a Code of Conduct. More at https://pydata.org/code-of-conduct/ This event will not be recorded or streamed.

⚡⚡Speak at PyData! ⚡⚡ We are always looking for speakers! Sign up here and we'll be in touch: https://forms.gle/kfFZ5hiqA9W57Ewg7 ⚡⚡Sponsor an event! ⚡⚡ PyData events are totally free and open to all! We have a broad reach to tech professionals of all kinds. We're always looking for sponsors and hosts for our events. Please get in touch if you're interested in supporting the community: [email protected]

Details

After a long time of hibernation, the PyData Zurich meetup is finally back! We would like to rekindle the community and provide regular meetups with talks revolving around all things data in the Python ecosystem. This will be our second edition.

Schedule:

6:00 Entry

6:15 Start

6:20 Talk #1

6:50 Q&A

7:00 Talk #2

7:30 Q&A

7:40 Apero

Talk #1: How (Not) to Use Fairness Metrics in ML - Michèle Wieland Machine learning is being used in critical decision-making processes, including lending, hiring and litigation. What makes machine learning so powerful is its ability to learn decision rules directly from training data and to apply those rules to make predictions. Therefore, if discriminatory biases are hidden in the training data, algorithms are likely to produce biased predictions. One approach to addressing the problem of bias and discrimination in ma chine learning involves using fairness metrics. This presentation provides an overview of how to apply fairness metrics in practice and highlights potential pitfalls to avoid when working with them.

Talk #2: Can We Squeeze() More Out of Python’s Type System? The Challenge of Tensor Shape Annotations - Eric Wolf Ever confused NHWC with NCHW tensor shapes? Misaligned axes can turn debugging into a nightmare. In this talk, we will push Python's type system to its limits. We'll explore the new variadic generics, delve into tensor shape arithmetic, and see where Python falls short compared to other languages and libraries.