cosine similarity

Author: veekaybee

content/docs/Recsys/_index.md

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-# Recsys Syllabus
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+weight: 2
+title: Recsys Syllabus
+---
+**Books**  
+
+1. [MMDM](http://www.mmds.org/)
+2. [Practical Recommender Systems](https://www.manning.com/books/practical-recommender-systems)
+3. [Recommener Systems, Aggarwal](https://www.amazon.com/Recommender-Systems-Textbook-Charu-Aggarwal-ebook/dp/B01DK3GZDY)
+4. [Practical Recommender Systems](https://www.manning.com/books/practical-recommender-systems)Falk
+
+**System design**
+- [Reading](https://eugeneyan.com/writing/system-design-for-discovery/)
+-  Google [Intro to Recsys Course](https://developers.google.com/machine-learning/recommendation)
+
+**Recsys Algorithms**
+- Collaborative Filtering Reading:[Amazon Paper](https://www.cs.umd.edu/~samir/498/Amazon-Recommendations.pdf)
+-  Collaborative Filter [Survey Paper](https://md.ekstrandom.net/pubs/cf-survey)
+- Matrix Factorization - Reading: [Netflix Prize paper](https://datajobs.com/data-science-repo/Recommender-Systems-%5BNetflix%5D.pdf)
+- Content Filtering - [Twitter Paper](https://link.springer.com/chapter/10.1007%2F978-3-642-20161-5_44)
+-  Hybrid Recommenders: [Collaborative + Content Based](https://aclanthology.org/W03-1103.pdf)
+ 
+**Methods**  
+- [Personalization](https://eugeneyan.com/writing/patterns-for-personalization) 
+    - [Multiarmed Bandits](https://www.youtube.com/watch?v=rDjCfQJ_sYY&t=17s)
+    - Embeddings [Overview](https://abhadury.com/articles/2020-03/embeddings-for-recommender-systems) and [Overview](https://drop.engineering/building-a-recommender-system-using-embeddings-de5a30e655aa)
+    - Random Walk - [Pixie](https://cs.stanford.edu/people/jure/pubs/pixie-www18.pdf)
+- Definitions of similarity/distance in personalized algos 
+- Candidate Generation Process
+- Candidate Ranking Process 
+
+ **Recsys Evaluation Metrics:** 
+- [Precision and Recall]()
+- [Overview](https://towardsdatascience.com/evaluation-metrics-for-recommender-systems-df56c6611093)
+- [Overview](https://www.jmlr.org/papers/volume10/gunawardana09a/gunawardana09a.pdf)
+- [Overview](https://beta-recsys.readthedocs.io/en/latest/notes/evaluation.html)
+- Precision/Recall/AUC 
+
+**Deep Learning Recsys**
+
+[tbd] [Softmax](https://developers.google.com/machine-learning/recommendation/dnn/softmax)
+
+**Recsys in Production**
+- [Spark ALS](https://spark.apache.org/docs/latest/ml-collaborative-filtering.html)
+- [Elasticsearch LTR](https://elasticsearch-learning-to-rank.readthedocs.io/en/latest/)
+- [Netflix and Scala for ML](https://portal.klewel.com/watch/webcast/scala-days-2019/talk/12/)
+- [Realtime Recs at Netflix](https://databricks.com/session/near-real-time-netflix-recommendations-using-apache-spark-streaming)
+- Netflix [Similariy](https://drive.google.com/file/d/1huRI4IimWVhF4tYLIoVqHHrTxKkV0imx/view)
+
+