Machine Learning

Rank-based Evaluator for Recommendations with Implicit Preference in PySpark

Implement a quality metric for recommendations with implicit preference based on the expected percentile ranking.

Map column values from strings to contiguous numbers in PySpark

Map string IDs to unique contiguous numeric IDs that are required by certain machine learning libraries.

Data Science London Scikit-learn Kaggle competition part III

Greedy forward feature selection performing badly on the specific problem.

Data Science London Scikit-learn Kaggle competition part II

Improving the SVM classification algorithm by running a grid search optimisation of the parameters.

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