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.