Recommendation Systems Training in Southampton

Recommendation Systems Training in Southampton

Recommender systems (also known as: recommendation systems, recommendation platform or recommendation engine) training.

Southampton

International House, Southampton International Business Park George Curl Way
Southampton, HAM SO18 2RZ
United Kingdom
Hampshire GB
Southampton
This centre occupies a great position - highly visible from the M27 motorway. The building's focal point is a beautiful atrium flooding the reception area with natural light. A comfortable, professional business lounge and a large breakout area where you can relax or network add to the welcoming... Read more

Recommendation Systems Course Events - Southampton

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
dsstne Amazon DSSTNE: Build a recommendation system Southampton 7 hours Thu, 2018-05-10 09:30 £1100 / £1350
dsstne Amazon DSSTNE: Build a recommendation system Southampton 7 hours Fri, 2018-06-29 09:30 £1100 / £1350
dsstne Amazon DSSTNE: Build a recommendation system Southampton 7 hours Fri, 2018-08-17 09:30 £1100 / £1350
dsstne Amazon DSSTNE: Build a recommendation system Southampton 7 hours Mon, 2018-10-15 09:30 £1100 / £1350

Course Outlines

Code Name Duration Outline
dsstne Amazon DSSTNE: Build a recommendation system 7 hours

Amazon DSSTNE is an open-source library for training and deploying recommendation models. It allows models with weight matrices that are too large for a single GPU to be trained on a single host.

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

Audience

  • Developers
  • Data scientists

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Other regions

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