Learn how to build a music recommendation system that suggests music artists using collaborative filtering and alternating least squares. In the process, you'll get a basic understanding of music recommendations, how Spotify recommends music, and how to use a production-ready collaborative filtering Python library called "implicit."

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Get the code:
https://github.com/musikalkemist/musiccollaborativefiltering

Last.fm music artist recommendation data set:
https://grouplens.org/datasets/hetrec-2011/

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Content

0:00 Introduction
0:28 Types of music recommendations
2:17 Spotify recommendation architecture
3:41 What are we building?
4:18 User Item Matrix
6:41 Alternating least squares
1:50 p.m. Last.fm dataset
4:46 p.m. Package overview
17:28 Data Loader Routine
8:30 p.m. Recovery artist
23:12 Implicit – a collaborative filtering library
23:47 Implementation of the recommendation system
27:55 Running artist recommendations
30:35 Join the The Sound of AI Slack community!

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