Sign up for our awesome SF Bay Area Tech Events weekly email newsletter.     EVENT DETAILS In the last year, there have been a lot of improvements done in the field of Machine Learning & the tools that support the community of developers. Still, implementing a recommender system is very hard. That is why at Crossing Minds, we have decided to create a series of four 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 The third meetup will be about evaluating different models for our recommender system. We will review the strategies we have to check if a model is under fitting or overfitting. After that, we will present & analyze the losses that are typically used in recommendation systems to train models. We will compare regression, classification, & rank based losses & when it's convenient to use each one. Finally, we are going to cover all the metrics that are typically used to evaluate the performance of different recommendation systems & how to test that the models are giving good results in production. Speaker Machine Learning Engineer at Crossing Minds, Ezequiel Esposito Agenda 6:30pm - 6:45pm Meet & Greet 6:45pm - 7:30pm Speakers 7:30pm - 8:00pm Q&A Additional Notes We'll have food. Lot of food!