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Specify ALS hyperparameters

You're now going to build your first implicit rating recommendation engine using ALS. To do this, you will first tell Spark what values you want it to try when finding the best model.

Four empty lists are provided below. You will fill them with specific values that Spark can use to build several different ALS models. In the next exercise, you'll tell Spark to build out these models using the lists below.

Cet exercice fait partie du cours

<cours>Building Recommendation Engines with PySpark</cours>
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Instructions de l’exercice

  • Fill in the following lists with the following values:
    • ranks = [10, 20, 30, 40]
    • maxIters = [10, 20, 30, 40]
    • regParams = [.05, .1, .15]
    • alphas = [20, 40, 60, 80]

Exercice interactif pratique

Essayez cet exercice en complétant ce code d’exemple.

# Complete the lists below
ranks = [____, ____, ____, ____]
maxIters = [____, ____, ____, ____]
regParams = [____, ____, ____]
alphas = [____, ____, ____, ____]
Modifier et exécuter le code