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It’s Not Just the Ad: How Meta Learned to Rank Everything Around It
2025-11-24 · 12:30
❄️ 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 🎟️ 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. ❄️❄️❄️ Session details: 💡 It’s Not Just the Ad: How Meta Learned to Rank Everything Around It 🗓️ Monday 24th November ⏰ 12:30 PM GMT 🗣️ Ayelet Lejtman, Staff Machine Learning Engineer at Meta Most recommendation systems focus on ranking the main item—whether it’s the perfect product, ad, or video. But in high-impact environments like Meta, optimizing the presentation of that item can be just as critical. Which image best complements an ad? Which text overlay (“Best Seller,” “Limited Time”) will drive engagement? These “non-product” recommendations are often overlooked, yet they can be harder to model than the primary recommendation itself. In this talk, I’ll share our team’s multi-year journey from early missteps to a robust, scalable ranking pipeline for creative elements that surround the main recommendation. We’ll explore: Data collection and labeling strategies tailored to secondary recommendation targets Model architectures and feature engineering approaches that work in large-scale environments Lessons learned on experimentation speed, evaluation metrics, and failure patterns Attendees will leave with actionable insights to design and deploy ranking models for any “artifact” that supports the main recommendation—whether in ads, e-commerce, or content platforms—so they can improve impact without overhauling their primary recommender system. ❄️❄️❄️ 🔗 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. 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 |
It’s Not Just the Ad: How Meta Learned to Rank Everything Around It
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