Building Recommendation Engines with PySpark

Updated on

Course overview

Provider
Datacamp
Course type
Free trial availiable
Deadline
Flexible
Duration
4 hours
Certificate
Available on completion
Course author
Jamen Long

Description

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
This course will show you how to build recommendation engines using Alternating Least Squares in PySpark. Using the popular MovieLens dataset and the Million Songs dataset, this course will take you step by step through the intuition of the Alternating Least Squares algorithm as well as the code to train, test and implement ALS models on various types of customer data.

Similar courses

Machine Learning
  • Flexible deadline
  • 61 hours
  • Certificate
Neural Networks and Deep Learning
  • Flexible deadline
  • 27 hours
  • Certificate
Introduction to Machine Learning in Production
  • Flexible deadline
  • 10 hours
  • Certificate
  • English language

  • Recommended provider

  • Certificate available