Recommendation systems are an invaluable tool. They are able to increase both customer experience and a company's profitability. Such systems work by recommending items that users will probably like, based on other items they have already liked. For example, when shopping for a smartphone on Amazon, accessories for that specific smartphone will be recommended. This improves the customer's experience (as they do not need to search for accessories), while it also increases Amazon's profits (for example, if the user did not know that there are accessories available for sale).
In this chapter, we will cover the following topics:
- Demystifying recommendation systems
- Neural recommendation systems
- Using Keras for movie recommendations
In this chapter, we will utilize the MovieLens dataset (available at http://files.grouplens.org/datasets...
