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Building Recommendation Engines by Suresh Kumar Gorakala

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Summary

In this chapter, we saw how recommendation engines are evolving and the motivations that are affecting the evolution of recommender systems, followed by a few potential use cases to watch out for. Finally, we touched upon some good methodologies, which should be considered before designing a recommender system. With this input, I'm sure that you are now equipped to confront the requirements of building future-ready recommendation engines which are self-learning, scalable, real-time, and futuristic. As mentioned in this chapter, deep learning can play a very important role in building more futuristic recommender systems.

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