DevConf.CZ 2019

Many of the applications you use and love provide personalised experiences to their users. This hands-on workshop will introduce the basics of recommendation as a class of machine-learning problems, introduce collaborative filtering algorithms, which are a popular way to capture the commonality between users’ interests, and explain how these algorithms work. You’ll learn practical details of using recommendation in your own applications, including: data preparation, tuning the training process to get the most out of recommendation engines, scaling training out with Apache Spark, handling both explicit data (e.g., ratings) and implicit data (e.g., page views or play counts), training and scoring models against streaming and batch data.