Building Recommendation Engines with PySpark

Course Overview

The Building Recommendation Engines with PySpark course teaches advanced machine learning techniques for personalized recommendation systems. Using scalable PySpark workflows and datasets like MovieLens and Million Songs, you will gain mathematical intuition and practical coding skills for the Alternating Least Squares (ALS) algorithm.

Who Is This Course For?

Targeted at advanced data scientists and Big Data engineers who want to build and evaluate recommendation systems on large customer datasets.

Key Takeaways

• Understand the intuition behind Alternating Least Squares (ALS).
• Train, test, and tune ALS models in PySpark.
• Work with real-world benchmark datasets including MovieLens and Million Songs.
• Deploy recommendation logic for diverse customer data scenarios.