Jun 18, 2024 · Jun 18, 2024
diff --git a/pgml-cms/docs/guides/supervised-learning.md b/pgml-cms/docs/guides/supervised-learning.md

 ### Training a Model

 Now that we've got data, we're ready to train a model using an algorithm. We'll start withthe default `linear` algorithmto demonstrate the basics. Seethe [Algorithms](../../../docs/training/algorithm\_selection/) for a complete list of available algorithms.
 Now that we've got data, we're ready to train a model using an algorithm. We'll start witha classification taskto demonstrate the basics. See[pgml.train](/docs/api/sql-extension/pgml.train/) for a complete list of available algorithms and tasks.

 ```postgresql
 SELECT * FROM pgml.train(
 (1 row)
 ```

 The output gives us information about the training run, including the `deployed` status. This is great news indicating training has successfully reached a new high score for the project's key metric and our new model was automatically deployed as the one that will be used to make new predictions for the project. See [Deployments](../../../docs/predictions/deployments/) for a guide to managing the active model.
 The output gives us information about the training run, including the `deployed` status. This is great news indicating training has successfully reached a new high score for the project's key metric and our new model was automatically deployed as the one that will be used to make new predictions for the project.

 ### Inspecting the results


 ### Example

 If you'vealready been through the [Training Overview](../../../docs/training/overview/), you can see the results of those efforts:
 If you'veexecuted the commands in this guide, you can see the results of those efforts:

 ```postgresql
 SELECT

 PostgresML will automatically deploy a model only if it has better metrics than existing ones, so it's safe to experiment with different algorithms and hyperparameters.

 Take a look at [Deploying Models](../../../docs/predictions/deployments/) documentation for more details.
 Take a look at [pgml.deploy](/docs/api/sql-extension/pgml.deploy) documentation for more details.

 ### Specific Models
Original file line number	Diff line number	Diff line change
Expand Up		@@ -46,7 +46,7 @@ target \|

		### Training a Model

		Now that we've got data, we're ready to train a model using an algorithm. We'll start withthe default `linear` algorithmto demonstrate the basics. Seethe [Algorithms](../../../docs/training/algorithm\_selection/) for a complete list of available algorithms.
		Now that we've got data, we're ready to train a model using an algorithm. We'll start witha classification taskto demonstrate the basics. See[pgml.train](/docs/api/sql-extension/pgml.train/) for a complete list of available algorithms and tasks.

		```postgresql
		SELECT * FROM pgml.train(
Expand DownExpand Up		@@ -79,7 +79,7 @@ INFO: Metrics: {
		(1 row)
		```

		The output gives us information about the training run, including the `deployed` status. This is great news indicating training has successfully reached a new high score for the project's key metric and our new model was automatically deployed as the one that will be used to make new predictions for the project. See [Deployments](../../../docs/predictions/deployments/) for a guide to managing the active model.
		The output gives us information about the training run, including the `deployed` status. This is great news indicating training has successfully reached a new high score for the project's key metric and our new model was automatically deployed as the one that will be used to make new predictions for the project.

		### Inspecting the results

Expand DownExpand Up		@@ -152,7 +152,7 @@ LIMIT 25;

		### Example

		If you'vealready been through the [Training Overview](../../../docs/training/overview/), you can see the results of those efforts:
		If you'veexecuted the commands in this guide, you can see the results of those efforts:

		```postgresql
		SELECT
Expand DownExpand Up		@@ -195,7 +195,7 @@ SELECT * FROM pgml.deployed_models;

		PostgresML will automatically deploy a model only if it has better metrics than existing ones, so it's safe to experiment with different algorithms and hyperparameters.

		Take a look at [Deploying Models](../../../docs/predictions/deployments/) documentation for more details.
		Take a look at [pgml.deploy](/docs/api/sql-extension/pgml.deploy) documentation for more details.

		### Specific Models

Expand Down