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 our training manager

    Fill out this quick form and we will contact you shortly




    You can modify your privacy settings and unsubscribe from our lists at any time (see our privacy policy).

    This site is protected by reCAPTCHA and the Google privacy policy and terms of service apply.

    Find us
    • 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
    Let us know how we can help

      Learn more

      You can modify your privacy settings and unsubscribe from our lists at any time (see our privacy policy).This site is protected by reCAPTCHA and the Google privacy policy and terms of service apply.