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Machine learning and statistical modeling allows us to answer questions such as:
What’s the likelihood that this user will buy from our website?
When will this mechanical part occur a critical failure?
What’s the credit risk of this customer?
This session provides an introduction to machine learning and predictive analytics and discusses how to implement such a predictive model, from access to data sources, data exploration, feature selection and creation, building training and testing sets, machine learning over data, model evaluation and experimentation – and finally – deploy the model as a service.
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