Data Scientists and Machine Learning Engineers often face the dilemma of “machine learning compared to deep learning” classifier usage for their business problems. Depending upon the nature of the dataset, some data scientists prefer classical machine-learning approaches. Others apply the latest deep learning models, while still others pursue an “ensemble” model hoping to get the best of both…
]]>Machine learning (ML) can extract deep, complex insights out of data to help make decisions. In many cases, using more advanced models delivers real business value through significantly improving on traditional regression models. Unfortunately, using traditional infrastructure to explain what drove a particular decision with a more advanced model can be difficult, time-consuming, and expensive.
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