The Ultimate Guide to Tech Stack for Indie Hackers in 2023

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

InfluxDB - Power Real-Time Data Analytics at Scale
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  • TensorFlow.NET

    .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

  • Yes, exactly. Since you will probably use scikit / tensorflow / pytorch with Python, you can call your model directly in a Django controller. Using other frameworks you will probably have to create a separate microservice with a model exposed via Rest API or use bindings like TensorFlow.NET

  • nodejs-storage

    Node.js client for Google Cloud Storage: unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archiving.

  • Also, in terms of packing a pre-trained model you will probably want to puts weights, biases etc into S3 or similar object storage (https://cloud.google.com/storage etc) and load it on application start

  • 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.

    InfluxDB logo
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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