/Predicting-game-sales-with-pyhton

The aim of this demonstration is to illustrate how regression models could be used to predict global game sales. I will use three regression models, including Lasso, Ridge and ElasticNet with cross validation tecnique.

Primary LanguageJupyter Notebook

Predicting game sales with pyhton

The aim of this demonstration is to illustrate how regression models could be used to predict global game sales. I will use three regression models, including Lasso, Ridge and ElasticNet with cross validation tecnique. I previously did the same analysis with the R program thus, the analysis also shows me how Pyhton works on the same data and compare their coding workflow.

Briefly, you can find:

  1. Basics of EDA and data processing techniques
  2. How to use standardization and polynominal features
  3. Tranformation of target variable with boxcox
  4. Regression with Cross Validation
  5. Interpreting rmse results
  6. Testing scale sensitivity

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