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The latest on Masterful and tips on Machine Learning

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Google Vertex vs Masterful AI (Part 2): Using unlabeled data

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Jack Lynch

In a previous post we compared Masterful AI’s computer vision training platform to Google’s Vertex AI AutoML platform.  We observed significant improvements across the board from Masterful. But that comparison only considered the use of labeled data, whereas Masterful—unlike Vertex—can also leverage your unlabeled data to improve performance, using semi-supervised learning (SSL).

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Hello World

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Sam Wookey

We're thrilled to announce that the Masterful AutoML platform is now available on the Python Package Index for everyone to use. Installation is as easy as pip install masterful. You get the full power of our deep learning platform to train your models to peak performance without manual tuning. With Masterful, developers can focus on solving problems with ML instead of wasting time and brain cells running endless training experiments.

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Four buckets of deep learning innovation: architecture, data, regularization, and optimization

Image of Yaoshiang Ho
Yaoshiang Ho


It’s hard to stay current and maintain competency in deep learning. It’s a young and fast growing field, which means that groundbreaking research and innovations are coming out really rapidly. But at Masterful, we don’t have a choice: we have to stay current because the promise we make to developers is that our platform automatically delivers state-of-the-art approaches for computer vision models (CV) in a robust and scalable way. 

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