Name: Webinar "How we built a recommendation system from scratch"
Start: 2022-11-09T17:00:00+02:00
End: 2022-11-09T18:00:00+02:00

The [Data Phoenix](https://dataphoenix.info/) team invites you all to our upcoming "[The A-Z of Data](https://dataphoenix.info/the-a-z-of-data/)" **charity webinar** that’s going to take place on **November 9, 2022 at 16.00 CET.**

* **Topic:** “Learning Through Machine Learning: How We Built a Recommendation System from Scratch”.
* **Speaker:** Dora Petrella, Senior Data Scientist at METRO.digital
* **Language:** English
* **Participation:** free (but you’ll be required to [register](https://www.eventbrite.com/e/webinar-how-we-built-a-recommendation-system-from-scratch-tickets-452539968227))
* **Karma perk:** [donate](https://go.koloua.com/dataphoenix) to our charity initiative

[REGISTER](https://www.eventbrite.com/e/webinar-how-we-built-a-recommendation-system-from-scratch-tickets-452539968227)

**ABOUT THE SPEAKER**
**Dora Petrella,** Senior Data Scientist at METRO.digital

Dora is a curiosity-driven Data Scientist with 4 years of experience. Her background is in Engineering and Computer Science, and she is currently based in Germany.

She chose to work for Metro.digital, the tech software company daughter of the international wholesaler Metro. Her Italian origins and her passion for everything around Machine Learning fit well in a company where food and technology meet together.

Dora contributed to different Machine Learning projects in the wholesale sector, such as recommendation systems, ranking problems in the context of product search, personalization in the context of marketing, and customer segmentation. Her main tasks are researching solutions, contributing to the implementation and monitoring of machine learning-based algorithms, and presenting results even to non-technical audiences.

*"We at Metro.digital have been building data science products for years and have gathered a fair amount of experience, especially in the area of recommendation systems. Over the last few months, my team’s been focusing on an exciting new challenge: building from scratch a machine learning-based recommendation system for real-time identification of substitute products. The resulting benefits are multiple: customers quickly discover more from our assortment; Metro employees reduce their time spent on manual search; and, Metro itself increases revenue and retains customers. The aim of this talk is to tell the story of our journey from concept to production, with a focus on our learnings, mistakes, and results."*

**ABOUT OUR CHARITY INITIATIVE**
This webinar is planned as **a charity event**. As we did before, we do our best **to raise funds for [KOLO](https://www.koloua.com/en) —** A project created by Ukrainian IT experts to help Ukraine fight the war against Russia by supplying high-tech equipment to the front lines.

This cause is very special to us. So, please donate any amount you can to help us save Ukrainian lives. **Every donation is a huge help!**

[Donate](https://go.koloua.com/dataphoenix)

*Please note that participation is free but registration is required! We are also looking forward to any [donations](https://go.koloua.com/dataphoenix) that you’re willing to give to our charity initiative.*

[REGISTER](https://www.eventbrite.com/e/webinar-how-we-built-a-recommendation-system-from-scratch-tickets-452539968227)

Dmitry Spodarets

Data Phoenix UA

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Webinar "How we built a recommendation system from scratch"

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Webinar "How we built a recommendation system from scratch"

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