Course Summary

You should now have a better understanding of how to:

  • Describe the purpose of recommendation systems.
  • Understand the components of a recommender 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.