The Data Science of Hyper-Parameter Tuning

The inner operations of advanced machine learning models are nebulous to the average business user, regulator, or customer impacted by the outputs of this form of statistical Artificial Intelligence. At best, such laymen are vaguely aware that neural networks, for example, function in a manner that's somewhat similar to how the human brain does. The most sophisticated may have heard something about the notion of parameters; most are blissfully unaware of the presence of hyper-parameters or their import to applications of deep learning. "Basically, in [these] machine learning models, there are two sets of parameters," explained Suman Bera, Senior Software Engineer at Katana Graph. "One set of parameters you are trying to learn through your machine learning algorithm. And, there is another set of parameters which are predefined. You are not trying to learn them. Hyper-parameters are invaluable to devising accurate predictions from advanced machine learning models, which are oftentimes ...