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Apache Spark ML

Distributed Machine Learning at scale with Spark MLlib.

Course Duration: 10 hours​

What You'll Learn​

  • Spark basics for ML
  • MLlib algorithms
  • Feature engineering at scale
  • Pipelines
  • Model training on clusters
  • Production deployment

Prerequisites​

  • Python/Scala
  • ML fundamentals
  • Big data basics

Course Modules​

  1. Introduction to Spark for ML
  2. Spark DataFrames
  3. MLlib Overview
  4. Feature Transformers
  5. Classification Algorithms
  6. Regression Algorithms
  7. Clustering
  8. ML Pipelines
  9. Cross-Validation
  10. Model Persistence
  11. Spark on Databricks
  12. Project: Large-scale ML Pipeline

Topics Covered​

  • Spark MLlib
  • Feature Engineering
  • Distributed Training
  • Databricks