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+Sebastian Raschka, 2015
+
+Python Machine Learning - Code Examples
+
+## Chapter 4 - Building Good Training Sets – Data Preprocessing
+
+- Dealing with missing data
+  - Eliminating samples or features with missing values
+  - Imputing missing values
+  - Understanding the scikit-learn estimator API
+- Handling categorical data
+  - Mapping ordinal features
+  - Encoding class labels
+  - Performing one-hot encoding on nominal features
+- Partitioning a dataset in training and test sets
+- Bringing features onto the same scale
+- Selecting meaningful features
+  - Sparse solutions with L1 regularization
+  - Sequential feature selection algorithms
+- Assessing feature importance with random forests
+- Summary