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Effective Amazon Machine Learning by Alexis Perrier

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Comparing performances

Keeping systems and applications simple is always difficult, but often worth it for the business. Examples abound with overloaded UIs bringing down the user experience, while products with simple, elegant interfaces and minimal features enjoy widespread popularity. The Keep It Simple mantra is even more difficult to adhere to in a context such as predictive analytics where performance is key. This is the challenge Amazon took on with its Amazon ML service.

A typical predictive analytics project is a sequence of complex operations: getting the data, cleaning the data, selecting, optimizing and validating a model and finally making predictions. In the scripting approach, data scientists develop codebases using machine ...

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