Recommendation Systems - Learn Python for Data Science #3 смотреть онлайн

In this video, we build our own recommendation system that suggests movies a user would like in 40 lines of Python using the LightFM recommendation library. I start off by talking about why we need recommendation systems, then we dive straight into installing our dependencies and writing our script.

The coding challenge for this video is here:

https://github.com/llSourcell/recommender_system_challenge

The winner of last weeks coding challenge (Rohan Verma):
https://twitter-sentiment-csv.herokuapp.com/
https://t.co/4eg8UdlaSB

The runner up (Arnaud Delauney):
https://github.com/arnauddelaunay/twitter_sentiment_challenge

I created a Slack channel for us, sign up here:
https://wizards.herokuapp.com/

The LightFM Python Library:
https://github.com/lyst/lightfm/tree/master/lightfm

Some great learning resources on recommender systems:

http://blogs.gartner.com/martin-kihn/how-to-build-a-recommender-system-in-python/

https://www.analyticsvidhya.com/blog/2015/08/beginners-guide-learn-content-based-recommender-systems/

http://www.quuxlabs.com/blog/2010/09/matrix-factorization-a-simple-tutorial-and-implementation-in-python/

http://blog.manugarri.com/a-short-introduction-to-recommendation-systems/

Best book to become a Python God:
https://learnpythonthehardway.org/

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