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Brain.js: This is a library for training and deploying neural networks in JavaScript. It provides a simple and flexible API for building feedforward and recurrent networks.
ML.js: This is a library for machine learning in JavaScript. It provides a wide range of algorithms including linear regression, k-means, and decision trees, as well as utility functions for data pre-processing and model evaluation.
Natural: This is a library for natural language processing in JavaScript. It provides a wide range of functionality for tasks such as tokenization, stemming, and sentiment analysis.
Synaptic: This is a library for building and training neural networks in JavaScript. It provides a flexible and modular architecture for building feedforward and recurrent networks.
If you really care about optimising this, you need, as other traders pointed out, a cache. Caches are a way of ensuring that the data you query stays in memory on a separate machine so you don't have the delay to disk & to commit. Things like memcached are created for this exact purpose. If you care about optimisation, look into it and other options. This is not a simple problem. Distributed systems like these are a whole area of work and research, so it won't be as simple as just swapping a DB, but if you care about performance, this is the path you have to go down eventually.
Have you checked out Streamlit at all? Seems like the new hotness for visualization and data access via the web in just Python.
JS for ML actually does exist https://github.com/facebookresearch/shumai