Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the ...

In this tutorial, we design an end-to-end, production-style analytics and modeling pipeline using Vaex to operate efficiently on millions of rows without materializing data in memory. We generate a ...

We make use of multi-stage docker builds so we can have into the same Dockerfile environments for testing and also for deploying our service.

Abstract: In the burgeoning landscape of online retail, effectively guiding users through vast product catalogs is paramount for enhancing user experience and driving sales. This paper details the ...

Abstract: Cardiovascular Health Forecaster Employing Flask is a cutting-edge online application that combines Python for its backend and Flask for its frontend. It anticipates heart disease risk with ...

A simple Flask application that can serve predictions machine learning model. Reads a pickled sklearn model into memory when the Flask app is started and returns predictions through the /predict ...

The ESP32-Stick-PoE-A-Cam(N16R8) is an open-source ESP32-S3 development board with Ethernet, camera, and active PoE support designed for machine learning applications. Compared to similar boards like ...