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Recommendation engines vs. predictions

If you have completed the prerequisites for this course, you will have worked with different machine learning models and predictive approaches. Therefore you may recognize that different tools and models are useful for different use cases.

We discussed what problems are best suited for recommendation engines in the opening lesson. Now it is your turn to distinguish between data-driven use cases that would fit under recommendation engines and those that would suit other statistical models.

This exercise is part of the course

Building Recommendation Engines in Python

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Hands-on interactive exercise

Turn theory into action with one of our interactive exercises

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