How to Visualize Machine Learning Models?

Banquet Hall

Machine learning algorithms are increasingly black-box models. However, their outputs are business data that humans need to understand and act upon. For example, if a clustering model suggests 4 customer clusters, how do we identify and characterize these? If a random forest model suggests a pattern of classification, how do we understand the dominant factors and the irrelevant ones? These topics fall under the umbrella of model visualization — where the inputs, process, and output of machine learning models are the topic of understanding. This talk explores some of the prevalent ways of visualizing machine learning models.

Machine Learning
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