* [14. Save / Load](machine-learning/14.-save-load.md)

<figure><img src="../.gitbook/assets/image (180).png" alt="" width="286"><figcaption></figcaption></figure>

1. Click on _**Pipeline**_ in the _**Machine Learning**_ category.

<figure><img src="../.gitbook/assets/image (181).png" alt="" width="563"><figcaption></figcaption></figure>

2. _**Pipeline**_: Choose the type of task:

* [Data Preparation](13.-pipeline.md#data-preparation)

* [Regression / Classification / GridSearch](13.-pipeline.md#regression-classification-gridsearch)

* [Clustering](13.-pipeline.md#clustering)

* [Dimension Reduction](13.-pipeline.md#dimension-reduction)

3. _**Code view**_: Preview the code that will be generated.

4. _**Run**_: Execute the code.

<figure><img src="../.gitbook/assets/image (182).png" alt="" width="563"><figcaption></figcaption></figure>

1. [_**Data Prep**_](3.-data-prep.md)

2. [_**Fit**_](10.-fit-predict.md)

3. [_**Transform**_](10.-fit-predict.md)

<figure><img src="../.gitbook/assets/image (183).png" alt="" width="563"><figcaption></figcaption></figure>

1. [_**Data Split**_](2.-data-split.md)

2. [_**Regressor**_ ](5.-regressor.md)_**/**_ [_**Classifier**_](6.-classifier.md) _**/**_ [_**GridSearch**_](9.-gridsearch.md)

3. [_**Fit**_](10.-fit-predict.md)

4. [_**Predict**_](10.-fit-predict.md)

5. [_**Evaluation**_](12.-evaluation.md)

<figure><img src="../.gitbook/assets/image (184).png" alt="" width="563"><figcaption></figcaption></figure>

1. [_**Clustering**_](7.-clustering.md)

2. [_**Fit**_](10.-fit-predict.md)

3. [_**Predict**_](10.-fit-predict.md)

4. [_**Transform**_](10.-fit-predict.md)

5. [_**Evaluation**_](12.-evaluation.md)

<figure><img src="../.gitbook/assets/image (185).png" alt="" width="563"><figcaption></figcaption></figure>

1. [_**Dimension Reduction**_](8.-dimension.md)

2. [_**Fit**_](10.-fit-predict.md)

3. [_**Transform**_](10.-fit-predict.md)

<figure><img src="../.gitbook/assets/image (186).png" alt="" width="287"><figcaption></figcaption></figure>

1. Click on _**Save/Load**_ in the _**Machine Learning**_ category.

<figure><img src="../.gitbook/assets/image (187).png" alt="" width="563"><figcaption></figcaption></figure>

2. Choose an action:

* [Save model](14.-save-load.md#save-model)

* [Load model](14.-save-load.md#load-model)

3. _**Code view**_: Preview the code that will be generated.

4. _**Run**_: Execute the code.

<figure><img src="../.gitbook/assets/image (188).png" alt="" width="563"><figcaption></figcaption></figure>

1. _**Target**_: Select the machine learning model to save.

2. _**Save path**_: Specify the path (location) to save the model. You can easily specify it by clicking on the folder icon.

<figure><img src="../.gitbook/assets/image (189).png" alt="" width="563"><figcaption></figcaption></figure>

1. _**Load path**_: Specify the path (location) where the model is saved. You can easily specify it by clicking on the folder icon.

2. _**Allocate to**_: Enter the variable name to assign to the loaded model.