Early in developing a machine learning project, it is tempting to focus primarily on building the model. Faith is placed in the notion that if the model is accurate, the other details will fall into place. This neglects the most crucial fact of all — the model is created to be used in the real world. The return on your AI investment can only be achieved when people use your model.
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With all the AI hype, it sometimes feels like a gold rush, which would make CloudFactory’s workforce solutions the picks and shovels. From those trenches, here are a few of our predictions for what 2021 will hold for AI and machine learning:
Read MoreQuality data is the lifeblood of great computer vision applications. But what happens when you don’t have enough data? In a previous article, we addressed your options for acquiring data sets for computer vision.
Read MoreIn 1910, it was preposterous to think that a manufacturer could produce and assemble automobiles quickly, with high quality, at scale. Today, business leaders have the opportunity to apply similar efficiencies to data labeling for machine learning.
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Whether you are a seasoned professional in this industry or just starting to dip your toes in, there is always more to learn about AI and machine learning.
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