Recommender Systems Hands on Workshop | Training Wide and Deep Recommenders | Day 2

Abstract

Day 2: Day 2: Training Wide and Deep Recommenders (120 mins) * Build a wide and deep network using TensorFlow 2: * Build a deep network using Keras. * Build a wide and deep network using TensorFlow feature columns. * Efficiently ingest training data with NVTabular data loaders. Break (15 mins) Day 2: Challenges of Deploying Recommendation Systems to Production (120 mins) * Deploy a recommender system in a production environment: * Acquire a trained model configuration for deployment. * Build a container for deployment. * Deploy the trained model using NVIDIA Triton Inference Server. Day 2: Final Review (15 mins) * Review key learnings and answer questions. * Learn to build your own training environment from the DLI base environment container. * Complete the assessment and earn a certificate. Take the workshop survey.

Shawn McCarthy

Graduate Instructor

Shawn McCarthy is a distinguished AI Committee Member and Vice President of Global Architecture, Big Data, and Information Risk at Manulife. He is currently pursuing a PhD, focusing on the impact of global events on market sentiment, and is developing an extensive model for market prediction and risk management. Additionally, as a Graduate Instructor at the University of Colorado, he fosters innovation and growth in future leaders. His work consistently echoes his professional motto Inspire Growth.