Machine Learning
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The news beat on AI continues as, “You must have it!” But now we also hear “companies are struggling with AI” too. One recent survey found that 71% of CFOs are "flying blind" and struggling to monetize AI. Initiatives built around a disruptive technology like AI are always challenging because both the technology and its applications are unfamiliar. In the case of AI they can also be abstract. “Work smarter not harder” is a great tagline, but “smarter” is hard to measure without standardized testing.
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My mind has been full of numbers lately. April has Tax Day, so I stress over my numbers and am usually disappointed at how they work out.
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In November, Tamarack expanded its AI team with the addition of Khrystyna Voloshyn as a data scientist.
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In her role as a data scientist, Voloshyn will support the development and optimization of Tamarack’s suite of AI products. This includes developing algorithms and models to support the machine learning (ML) processes that drive Tamarack Predictors, using ML to classify and categorize customer data, and developing new products and tools to keep Tamarack at the forefront of the industry.
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Quoc (Tom) Huynh may have only joined Tamarack a few months ago, but he is already making a big impact. In his role as senior data engineer, Tom spends his time increasing the company’s data integration, analysis and machine learning/AI capabilities for Tamarack’s AI product suite.
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In his role as a senior data engineer, Huynh will focus his time on increasing the company’s data integration, analysis and machine learning/AI capabilities for Tamarack’s AI product suite.
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