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Merge pull request #3646 from mbellitti/patch-1
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Fixed dead links in Tutorial docs
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Yard1 committed Jul 22, 2023
2 parents fa8cb5e + 80fe7cb commit c4cb387
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23 changes: 13 additions & 10 deletions docs/source/tutorials.rst
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Expand Up @@ -5,30 +5,33 @@ Classification
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Learn how to prepare the data for modeling, create a classification model, tune hyperparameters of a model, analyze the performance, and consume the model for predictions.

- `Binary Classification Tutorial - Level Beginner (CLF101) <https://github.com/pycaret/pycaret/blob/master/tutorials/Binary%20Classification%20Tutorial%20Level%20Beginner%20-%20%20CLF101.ipynb>`_

- `Binary Classification Tutorial - Level Intermediate (CLF102) <https://github.com/pycaret/pycaret/blob/master/tutorials/Binary%20Classification%20Tutorial%20Level%20Intermediate%20-%20CLF102.ipynb>`_

- `Multiclass Classification Tutorial - Level Beginner (MCLF101) <https://github.com/pycaret/pycaret/blob/master/tutorials/Multiclass%20Classification%20Tutorial%20Level%20Beginner%20-%20MCLF101.ipynb>`_
- `Binary Classification Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Binary%20Classification.ipynb>`_

- `Multiclass Classification Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Multiclass%20Classification.ipynb>`_

Regression
**************
Learn how to prepare the data for modeling, create a regression model, tune hyperparameters of a model, evaluate model errors, and consume the model for predictions.

- `Regression Tutorial - Level Beginner (REG101) <https://github.com/pycaret/pycaret/blob/master/tutorials/Regression%20Tutorial%20Level%20Beginner%20-%20REG101.ipynb>`_

- `Regression Tutorial - Level Intermediate (REG102) <https://github.com/pycaret/pycaret/blob/master/tutorials/Regression%20Tutorial%20Level%20Intermediate%20-%20REG102.ipynb>`_
- `Regression Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Regression.ipynb>`_

Clustering
**************
Learn how to prepare the data for modeling, create a K-Means clustering model, assign the labels, analyze results, and consume a trained model for predictions on unseen data.

- `Clustering Tutorial - Level Beginner (CLU101) <https://github.com/pycaret/pycaret/blob/master/tutorials/Clustering%20Tutorial%20Level%20Beginner%20-%20CLU101.ipynb>`_
- `Clustering Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Clustering.ipynb>`_


Anomaly Detection
*****************
Learn how to prepare the data for modeling, create an unsupervised anomaly detector, evaluate the results of the trained model, and consume the model for predictions on unseen data.

- `Anomaly Detection Tutorial - Level Beginner (ANO101) <https://github.com/pycaret/pycaret/blob/master/tutorials/Anomaly%20Detection%20Tutorial%20Level%20Beginner%20-%20ANO101.ipynb>`_
- `Anomaly Detection Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Anomaly%20Detection.ipynb>`_


Time Series Forecasting
***********************
Learn how to prepare the data for modeling, create and compare a time series model, analyze it, use it to make predictions, and save the model.


- `Time Series Forecasting Tutorial <https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Time%20Series%20Forecasting.ipynb>`_

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