In the last years a lot of improvements were done in the field of Machine Learning and the Tools that support the community of developers. But still, implementing a recommender system is very hard. That is why at Crossing Minds, we decided to create a series of 4 meetups to discuss how to implement a recommender system end-to-end:

Part 1 – The Right Dataset
Part 2 – Model Training
Part 3 – Model Evaluation
Part 4 – Real-Time Deployment

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This second meetup will be about training different models for our recommender system. We will review the simple models we can build as a baseline. After that, we will present the recommender system as an optimization problem and discuss different training losses. We will mention linear models and matrix factorization techniques. We will end the presentation with a simple introduction to non-linear models and deep learning.