Build a real-time feature pipeline in Python, step-by-step

Machine Learning models are as good as the input features you feed at training and inference time. And for many real-world applications, like financial trading, these features must be generated and served as fast as possible, so the ML system produces the best predictions possible. Generating and serving features fast is what a real-time feature pipeline does. Can …

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3 steps to transform an ML prototype into a real-world ML app

Training Machine Learning models inside notebooks is just one step to building real-world ML services. And as exciting as it is, it brings no business value unless you deploy and operationalize the model, as a real-world ML app. In this article, you will learn how to transform an all-in-one Jupyter notebook with data preparation and …

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Real-time feature engineering with Python

Real-time ML is a fascinating topic, which I wanna go deeper into in the following weeks and months. Because of this, I started creating a sequence of small projects where I build real-time products, beginning with a real-time feature engineering pipeline. Real-time feature engineering A real-time feature pipeline is a program that ingests real-time raw data (e.g. …

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