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[D] Using DVC for data projects – efficient versioning for inputs, intermediate files and algorithm models with no longer need to think about how to store data for collaboration

In the following aritcle Qonto data team explains how DVC helped them dealing with production data files such as trained machine learning algorithms and provided a reliable way of versioning those files along the project development: Using DVC to create an efficient version control system for data projects

DVC brought versioning for inputs, intermediate files and algorithm models and this drastically increased productivity by providing a clean framework to manage data in an effortless way to split a project into atomic steps.

To make it more concrete, Quonto illustrated this article with a real project on VAT auto-detection from receipts – it consists in automatically retrieving the value-added tax amount from a receipt document in order to simplify accounting work.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.