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Artificial Intelligence Blog
Suppose you’re the owner of a popular online clothing store and you’d like to increase sales. An employee suggested that a “red” buy button icon will result in more clicks than a “blue” one. To empirically settle the question of which icon color yields more clicks, you decide to run a test. The standard approach to testing of this sort is A/B testing and involves the following:
The usage of hyperparameter techniques has helped many machine learning experts automate the burden of manual empiric experiments to find the optimal (or close to) combination of hyperparameters for a model. With the first publications about the usage of algorithms to do this task dating from the early 2010s, it's safe to assume this is a new area that we're improving on at high speed.
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