Duration
7 hours (usually 1 day including breaks)
Requirements
- Hands-on experience with Deep Learning machine learning models
Audience
- Developers
- Data scientists
Overview
In this instructor-led, live training, participants will learn how to use DSSTNE to build a recommendation application.
By the end of this training, participants will be able to:
- Train a recommendation model with sparse datasets as input
- Scale training and prediction models over multiple GPUs
- Spread out computation and storage in a model-parallel fashion
- Generate Amazon-like personalized product recommendations
- Deploy a production-ready application that can scale at heavy workloads
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Course Outline
To request a customized course outline for this training, please contact us.