Numerical machine learning algorithms attempt to find structure
in data. Approaches range from using parametric models such
as neural networks to using non-parametric models. This talk
will explore the differences between batch learning applications
in which a fixed training set is used and continuous learning
in which new data is continuously added to the training set.
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