The app for independent voices
If you want to get hands-on experience with a cutting-edge recommender system project, I've got good news for you...
We've just released the third lesson of our 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻 𝗛&𝗠 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗲𝗿 𝗰𝗼𝘂𝗿𝘀𝗲 written by Anca Ioana Muscalagiu.
In this lesson, we explore the training pipeline for building and deploying effective personalized recommenders.
By the end of it, you'll learn how to:
- Master the two-tower network architecture used in cutting-edge real-time recommenders
- Leverage Hopsworks feature store for loading the training dataset optimized for high throughput
- Train and evaluate the two-tower network and ranking model
- Upload and manage models in the Hopsworks model registry
- Use MLOps best practices
🔗 Get started with Lesson 3 on Decoding ML:
Feel free to share your thoughts or questions in the comments below.
Let’s build together!
Thank you, Anca Ioana Muscalagiu, for writing this amazing lesson!
