Today I studied preprocessing for basic learning models. - Dropping and imputing missing values (dropna, SimpleImputer) - Handling categorical data (mapping ordinal features, one-hot encoding nominal features and its downsides) - Splitting and scaling datasets Next time I'll put it into practice with the Titanic CSV! I'd like to try Kaggle too. #ML
// notes
Daily Notes
A log of short thoughts and notes.
Today I studied the basic learning models, perceptron and ADALINE, plus KNN, decision trees, random forests, and logistic regression. I skipped over a fair amount of the math, so next time I'll go deeper. Random forests are nice. #ML