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There is several techniques that could work for you: Target Encoder: Works well when there is a high cardinality of a categorical feature. Ordinal/Label Encoding: Tradition label encoding Weight Of Evidence: tells the predictive power of an independent variable in relation to the dependent variable


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Things I care about a lot: list comprehensions instead of loops use apply + lambda functions when forced to iterate operations on pandas dataframes use @tf.function decorator on top of TensorFlow functions to speed up computation use as much SQL as possible when importing data from databases, to avoid doing the same stuff in Python


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