2023-04-17 –, B07-B08
What is a ML platform and do you even need one? When should you consider investing in your own ML platform? What challenges can you expect building and maintaining one? Tune in and discover (some) answers to these questions and more! I will share a first-hand account of our ongoing journey towards becoming a ML platform team within Delivery Hero's Logistics department, including how we got here, how we structure our work, and what challenges and tools we are focussing on next.
What is an ML platform and do you even need one? When should you consider investing in your own ML platform? What challenges can you expect building and maintaining one? Tune in and discover (some) answers to these questions and more! I will share a first-hand account of our ongoing journey towards becoming an ML platform team within Delivery Hero's Logistics department, including how we got here, how we structure our work, and what challenges and tools we are focusing on next.
Novice
Expected audience expertise: Python –Novice
Abstract as a tweet –What is a ML platform and do you even need one? When should you consider investing in your own ML platform? What challenges can you expect building and maintaining one? Join my talk at PyData to hear how we are cooking up our own ML platform at @Delivery Hero!
I am leading a scrappy but growing team of ML engineers at Delivery Hero who aim to bridge the gap between software engineering, DevOps, data engineering, and data science. I hope to make data science easier without restricting the creativity and flexibility that data scientists need to make an impact in their role.