Course recap

Building Recommendation Engines with PySpark

Jamen Long

Data Scientist at Nike

Course summary

Three types of data
  • Explicit Ratings
  • Implicit Ratings using user behavior counts
  • Implicit Ratings using binary user behavior
Building Recommendation Engines with PySpark

Things to bear in mind

  • The more data the better
Building Recommendation Engines with PySpark

Things to bear in mind (cont.)

  • The more data the better
  • The best model evaluation is whether actual users take your recommendations
Building Recommendation Engines with PySpark

Resources

Building Recommendation Engines with PySpark

Let's practice!

Building Recommendation Engines with PySpark

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