[P] I trained an AI model on 120M+ songs from iTunes

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

Scout Monitoring - Free Django app performance insights with Scout Monitoring
Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.
www.scoutapm.com
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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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  • txtai

    💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

    If you're using FAISS, you may want to take a look at txtai in the future (https://github.com/neuml/txtai). You can combine a FAISS index with a SQLite database to add additional field based filtering.

  • Scout Monitoring

    Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

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  • qdrant

    Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

    Have you considered a proper vector database with filtering already built-in? Some tools like Qdrant (https://qdrant.tech) can perform vector search with metadata filtering, and you can quickly scale them up, as they are proper databases, not libraries like FAISS. I may give you a quick tour, if you want ;)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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