GITBOOK-118: fix links

Author: Daniel Illenberger

pgml-cms/docs/introduction/apis/sql-extensions/pgml.train/data-pre-processing.md

@@ -25,11 +25,11 @@ In this example:
 
 There are 3 steps to preprocessing data:
 
-* [Encoding](../../../../../../pgml-dashboard/content/docs/training/preprocessing.md#categorical-encodings) categorical values into quantitative values
-* [Imputing](../../../../../../pgml-dashboard/content/docs/training/preprocessing.md#imputing-missing-values) NULL values to some quantitative value
-* [Scaling](../../../../../../pgml-dashboard/content/docs/training/preprocessing.md#scaling-values) quantitative values across all variables to similar ranges
+* [Encoding](data-pre-processing.md#categorical-encodings) categorical values into quantitative values
+* [Imputing](data-pre-processing.md#imputing-missing-values) NULL values to some quantitative value
+* [Scaling](data-pre-processing.md#scaling-values) quantitative values across all variables to similar ranges
 
-These preprocessing steps may be specified on a per-column basis to the [train()](../../../../../../docs/training/overview/) function. By default, PostgresML does minimal preprocessing on training data, and will raise an error during analysis if NULL values are encountered without a preprocessor. All types other than `TEXT` are treated as quantitative variables and cast to floating point representations before passing them to the underlying algorithm implementations.
+These preprocessing steps may be specified on a per-column basis to the [train()](./) function. By default, PostgresML does minimal preprocessing on training data, and will raise an error during analysis if NULL values are encountered without a preprocessor. All types other than `TEXT` are treated as quantitative variables and cast to floating point representations before passing them to the underlying algorithm implementations.
 
 ```sql
 SELECT pgml.train(