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A Comparison of Two Popular Machine Learning Techniques Machine learning ML has grown exponentially as a field, but a familiar roadblock remains for many businesses: data. High-quality training data is the foundation needed to run successful AI and ML models and yet quality assurance is often an overlooked critical Michigan of the data labeling process. Our goal with the report is to provide a current picture of the trends, priorities, and challenges faced by businesses building AI technology.
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