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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.

Questo esercizio fa parte del corso

Building Recommendation Engines with PySpark

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Istruzioni dell'esercizio

  • 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]

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Complete the lists below
ranks = [____, ____, ____, ____]
maxIters = [____, ____, ____, ____]
regParams = [____, ____, ____]
alphas = [____, ____, ____, ____]
Modifica ed esegui il codice