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The Right Humans in the Right Loops: A Fashionable Use Case

The Right Humans in the Right Loops: A Fashionable Use Case

You’ve heard us say it many times: Human input is a vital part of the machine learning computing loop. To get the quality and accuracy required to successfully employ machine-learning-fueled applications, human knowledge is critical for training and retraining the algorithms.

Our recent collaboration with the folks at Algorithmia, our Seattle neighbors who help “developers build intelligent applications by providing a common API for algorithms, functions and models that are accessible and discoverable to anyone,” illustrates this well. Algorithmia built a human-in-the-loop deep learning workflow for a fashion classifier and deployed it at scale; our awesome community did the labeling for the training data. Check out this great recap of the project from Diego Oppenheimer, Algorithmia’s founder and CEO: Machine Learning with Humans in the Loop.

image credit: libreshot.com