In the Datamine Guide to Predictive and AI Modelling, we look at the model development process, the benefits and the issues involved with this type of complex analytics.
Predictive modelling is the process of using past data to determine, statistically, what is likely to happen in the future under the assumption that past trends will continue to apply. Many (if not most) AI and Machine Learning programmes incorporate some form of predictive modelling, as the applications ‘learn’ through looking at past data to inform future events.
This guide does not instruct people on how to build these models, but it covers the steps involved and the practical issues to consider.
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