Industrial recommender systems (RecSys) are made up of complex pipelines requiring multiple steps including data preprocessing and feature engineering, building and training recommender models and deploying them into production. Data Scientists and ML engineers might focus on different stages of recommender systems, however they share a common desire to reduce the time and effort searching for and combining boilerplate code coming from different sources or writing custom code from scratch to create their own RecSys pipelines.

In this presentation, we will first touch upon main challenges of building and deploying RecSys, and then introduce NVIDIA Merlin framework that consists of a set of libraries and tools to help RecSys practitioners build models and pipelines more easily and efficiently. We will conclude the presentation with a short demo of building and training recommender models with Merlin Models library, a component of the Merlin framework, designed to simplify the development and even deployment of recommender models.

Lucky draw prizes

We will raffle 5 winners for the book during the event. To enter the lucky draw, please complete one of the two steps:
- Twitter the event with hashtag #recaicamp and tag @aicampai . for example:

#recaicamp online AI/ML tech talk series by @aicampai: @ak_ronay and Benedikt will discuss building end-to-end recommender systems with Nvidia Merlin @NVIDIAAI. Free RSVP: https://www.aicamp.ai