You may not believe this, but you have all the tools and knowledge required for working in industrial Data Science. You have analyzed the data to find the patterns. You can write pipelines, and deploy models into production.
Here, we will show you how these skills can be used in conjunction with each other to solve real world problems. You will improve the recommender system - but now, without handholding.
Data Science is a very dynamic field, so one of the parts of work of a data scientist is reading scientific papers.
Here, we present several papers which can be used to improve the recommender system, as well as short summaries of these papers.
Reflect on how these papers correlate with your findings at Lesson 7. Which approach should improve the metrics the most? Implement the approach described in one of the papers discussed above.