Recommendation systems

Machine learning training

Prerequisites

Python syntax
Solid knowledge of basic machine learning ideas
(validation methods, gradient descent algorithm, preventing overfitting)
Machine learning experience

Skills your team will gain

An understanding of popular types of recommendation systems and state-of-the-art results.

Practical skills for building high-quality recommendation systems.

Duration

1 day

Agenda

Part 1

Overview

  • Collaborative filtering, a content-based approach
  • Low-rank matrix factorization

Part 2

Case study in PyTorch

  • User-based k-Nearest Neighbors
  • AR, ARMA, ARIMA
  • SVD
  • SGD-based efficient embedding

Contact us

Locations
  • deepsense.ai, Inc.
  • 2100 Geng Road, Suite 210
  • Palo Alto, CA 94303
  • United States of America
  • deepsense.ai Sp. z o.o.
  • al. Jerozolimskie 44
  • 00-024 Warsaw
  • Poland
  • ul. Łęczycka 59
  • 85-737 Bydgoszcz
  • Poland
Let us know how we can help