Recommendation Systems without the fuss
summary
Practical introduction to recommendation systems covering core techniques and recent deep learning architectures. Includes hands-on examples in Python using TensorFlow and Google ML Engine, plus datasets to practice building a news/article recommendation scenario.
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chapters (17)
- 0:00Introduction to recommendation systems
- 1:12What are recommendation systems
- 3:38ML techniques for recommendation
- 5:00Collaborative filtering explained
- 6:46Matrix factorization in recommendation
- 9:01Collaborative filtering limitations
- 11:52Content-based filtering
- 13:16Hybrid recommendation systems
- 15:24Demo: simple recommendation system
- 17:29Evaluating recommendation systems
- 21:03Deep learning for recommendation
- 23:30News recommendation challenges
- 25:36PhD research in recommendation
- 31:59Neural architecture for news
- 35:15Research data and results
- 37:45Evaluation and benchmarks
- 39:11Conclusion
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