No ML book is complete without mentioning recommendation engines—probably one of the most well known applications of ML. In part, this is thanks to the publicity gained when Netflix announced a $1 million competition for movie rating predictions, also known as recommendations. Add to this Amazon's commercial success in making use of it.
The goal of recommendation engines is to predict the likelihood of someone wanting a particular product or service. In the context of Netflix, this would mean recommending movies or TV shows to its users.
One intuitive way of making recommendations is to try and mimic the real world, where a person is likely to seek recommendations from like-minded people. What constitutes ...
