
Online Learning: The Challenging Data Frontier - yassien
https://growingdata.com.au/online-learning-the-challenging-data-frontier/
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yassien
Online learning is a subfield of machine learning where practitioners
sometimes refer to as incremental or out-of-core learning where machines need
to continuously learn and predict in real-time. Lately, this field is gaining
more attention, especially with the continuous training and deployment of
machine learning models. According to the traditional learning paradigm, data
becomes available in sequentially incremental order to update predictors for
future data at each step or point in time. This is opposing to the
conventional batch learning techniques which generate the best predictor by
learning on the entire training data set at once. Compared to “traditional” ML
solutions, online learning is a fundamentally different approach, one that
embraces the fact that learning environments can (and do) change over time.
Ideally, we need a model that not just predicts in real-time, but learns in
real-time.

