Chapter 7. Recommendations on Spark
In this chapter, we will switch our focus to SPSS on Apache Spark as SPSS is a widely used tool for machine learning and data science computing.
Specifically, in this chapter, with a process similar to what we used in previous chapters, we will start with discussing setting up our SPSS on a Spark system for a recommendation project, together with a full description of this real-life project. Then, we will select machine learning methods and prepare the data. With SPSS Analytic Server, we will estimate models on Spark and then evaluate models with a focus on using error ratios. Finally, we will deploy the models for our client. Here are the topics that will be covered in this chapter:
- Spark for a recommendation engine
- Methods for recommendation development
- Data treatment
- Model estimation
- Model evaluation
- Recommendation deployment
