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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.

Este exercício faz parte do curso

Building Recommendation Engines with PySpark

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Instruções do exercício

  • 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]

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Complete the lists below
ranks = [____, ____, ____, ____]
maxIters = [____, ____, ____, ____]
regParams = [____, ____, ____]
alphas = [____, ____, ____, ____]
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