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neuralmaticv wants to merge 4 commits into pycaret:main

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docs update - fixed broken links #2

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fix anchor link

neuralmaticv Aug 20, 2022

fixed broken links

neuralmaticv Aug 20, 2022

fixed broken links

neuralmaticv Aug 20, 2022

Merge branch 'main' into main

neuralmaticv Jan 7, 2024

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4 changes: 2 additions & 2 deletions README.md

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Expand Up		@@ -74,9 +74,9 @@ PyCaret and its Machine Learning capabilities are seamlessly integrated with env

		### Time Series

	PyCaret new time series module is now available in the `3.0-rc`. Staying true to the simplicity of PyCaret, it is consistent with the existing API and fully loaded with functionalities. Statistical testing, model training and selection (30+ algorithms), model analysis, automated hyperparameter tuning, experiment logging, deployment on cloud, and more. All of this with only a few lines of code. If you would like to give it a try, check out our official [quick start](https://nbviewer.org/github/pycaret/pycaret/blob/time\_series\_beta/time\_series\_101.ipynb) notebook.
	PyCaret new time series module is now available in the `3.0-rc`. Staying true to the simplicity of PyCaret, it is consistent with the existing API and fully loaded with functionalities. Statistical testing, model training and selection (30+ algorithms), model analysis, automated hyperparameter tuning, experiment logging, deployment on cloud, and more. All of this with only a few lines of code. If you would like to give it a try, check out our official [quick start](https://nbviewer.org/github/pycaret/pycaret/blob/master/examples/time_series/forecasting/time_series_101.ipynb) notebook.
Copy link Collaborator @ngupta23 ngupta23 Aug 21, 2022 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others. Learn more. I Am wondering if we should change the link to the folder now that we have multiple files there: https://nbviewer.org/github/pycaret/pycaret/tree/master/examples/time_series/forecasting/ Copy link Author @neuralmaticv neuralmaticv Aug 21, 2022 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others. Learn more. That would be a better option, but in that case, I think that notebook names should be more informative. Copy link Collaborator @ngupta23 ngupta23 Aug 21, 2022 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others. Learn more. How about this in that case? It has more information about the notebooks. https://pycaret.gitbook.io/docs/get-started/tutorials Copy link Author @neuralmaticv neuralmaticv Aug 22, 2022 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others. Learn more. Yes, I think that would be fine.

	* 📚 [Time Series Docs](https://pycaret.readthedocs.io/en/time\_series/api/time\_series.html)
	* 📚 [Time Series Docs](https://pycaret.readthedocs.io/en/latest/api/time_series.html)
		* ❓ [Time Series FAQs](https://github.com/pycaret/pycaret/discussions/categories/faqs?discussions\_q=category%3AFAQs+label%3Atime\_series)
		* 🚀 [Features and Roadmap](https://github.com/pycaret/pycaret/issues/1648)

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6 changes: 3 additions & 3 deletions get-started/modules.md

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Expand Up		@@ -68,12 +68,12 @@ Association rule learning is a rule-based machine learning method for discoverin
		{% endtab %}

		{% tab title="Time Series" %}
	### [Time Series (beta)](quickstart.md#time-series-beta)
	### [Time Series (beta)](quickstart.md#time-series)

		Time series forecasting is the process of analyzing time series data using statistics and modeling to make predictions and inform strategic decision-making

	* **[Quickstart](quickstart.md#time-series-beta)**
	* **[API Docs](https://pycaret.readthedocs.io/en/time\_series/api/time\_series.html)**
	* **[Quickstart](quickstart.md#time-series)**
	* **[API Docs](https://pycaret.readthedocs.io/en/latest/api/time_series.html)**
		* **[Tutorial**](tutorials.md)
		{% endtab %}

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2 changes: 1 addition & 1 deletion get-started/quickstart.md

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Expand Up		@@ -18,7 +18,7 @@ Select your use case:
		* [Anomaly Detection](quickstart.md#anomaly-detection)
		* [Natural Language Processing](quickstart.md#natural-language-processing)
		* [Association Rules Mining](quickstart.md#association-rules-mining)
	* [Time Series (beta)](quickstart.md#time-series-beta)
	* [Time Series (beta)](quickstart.md#time-series)

		## Classification

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