Recommendation Systems – Google

Interested in Machine Learning ? This free online course on Recommendation Systems from Google experts is the best place to start.

Google’s Recommendation Systems course description

What you will learn:

  • Describe the purpose of recommendation systems.
  • Understand the components of a recommendation system including candidate generation, scoring, and re-ranking.
  • Use embeddings to represent items and queries.
  • Develop a deeper technical understanding of common techniques used in candidate generation.
  • Use TensorFlow to develop two models used for recommendation: matrix factorization and softmax.

Course content

  • Background
    • Large-Scale Recommendation Systems
    • Terminology
    • Recommendation systems overview
  • Candidate Generation
    • Content-based filtering
    • Collaborative filtering and matrix factorization
    • Deep neural network models
  • Retrieval, scoring, re-ranking

Data Science

Prerequisites

This course assumes you have:

Course details

  • Institution: Google
  • Level: Intermediate
  • Language: English
  • Duration: 4 hours, self-paced
  • Provider: Google Developers

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