Repository: sktime/sktime
Pull request: [DOC] Improvements to formulations in the README
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#### Reference Issues/PRs
Fixes #4755 
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#### What does this implement/fix? Explain your changes.
Some Spell Changes and Enhancements
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No

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#### What should a reviewer concentrate their feedback on?
Readme section

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No

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##### For all contributions
- [ ] I've added myself to the [list of contributors](https://github.com/sktime/sktime/blob/main/CONTRIBUTORS.md) with any new badges I've earned :-)
  How to: add yourself to the [all-contributors file](https://github.com/sktime/sktime/blob/main/.all-contributorsrc) in the `sktime` root directory (not the `CONTRIBUTORS.md`). Common badges: `code` - fixing a bug, or adding code logic. `doc` - writing or improving documentation or docstrings. `bug` - reporting or diagnosing a bug (get this plus `code` if you also fixed the bug in the PR).`maintenance` - CI, test framework, release.
  See here for [full badge reference](https://allcontributors.org/docs/en/emoji-key)
- [ ] Optionally, I've added myself and possibly others to the [CODEOWNERS](https://github.com/sktime/sktime/blob/main/CODEOWNERS) file - do this if you want to become the owner or maintainer of an estimator you added.
  See here for further details on the [algorithm maintainer role](https://www.sktime.net/en/latest/get_involved/governance.html#algorithm-maintainers).
- [x] The PR title starts with either [ENH], [MNT], [DOC], or [BUG]. [BUG] - bugfix, [MNT] - CI, test framework, [ENH] - adding or improving code, [DOC] - writing or improving documentation or docstrings.

##### For new estimators
- [ ] I've added the estimator to the API reference - in `docs/source/api_reference/taskname.rst`, follow the pattern.
- [ ] I've added one or more illustrative usage examples to the docstring, in a pydocstyle compliant `Examples` section.
- [ ] If the estimator relies on a soft dependency, I've set the `python_dependencies` tag and ensured
  dependency isolation, see the [estimator dependencies guide](https://www.sktime.net/en/latest/developer_guide/dependencies.html#adding-a-soft-dependency).


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Problem statement:
[DOC] improve formulations and user experience of repo README
#### Describe the issue linked to the documentation
I would like to enhance certain sections to give them a more professional feel.
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Tell us about the confusion introduced in the documentation.
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Hints from issue discussion:
@ksachdeva  Could you please assign me to this issue, or should I proceed to raise a pull request directly?
Sure! Can you expand in more detail which sections you would like to work on?
The introductory lines for the "Features" and "Where to ask questions" section
"Questions and feedback are extremely welcome! Please understand that we won't be able to provide individual support via email. We also believe that help is much more valuable if it's shared publicly, so that more people can benefit from it."

"Our aim is to make the time series analysis ecosystem more interoperable and usable as a whole. sktime provides a unified interface for distinct but related time series learning tasks. It features [dedicated time series algorithms](https://www.sktime.net/en/stable/estimator_overview.html) and tools for composite model building including pipelining, ensembling, tuning and reduction that enables users to apply an algorithm for one task to another."



There appear to be some minor spelling errors that I would be happy to rectify.
sure, please go ahead!

Commit message: Update README.md

Patch to review:
diff --git a/README.md b/README.md
index 5f2232b4325..ae21e48d3d3 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,12 @@
 <a href="https://www.sktime.net"><img src="https://github.com/sktime/sktime/blob/main/docs/source/images/sktime-logo.svg" width="175" align="right" /></a>
 
-# Welcome to sktime
+# Welcome to sktime :hugs:
 
 > A unified interface for machine learning with time series
 
 :rocket: **Version 0.19.2 out now!** [Check out the release notes here](https://www.sktime.net/en/latest/changelog.html).
 
-sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation and forecasting. It comes with [time series algorithms](https://www.sktime.net/en/stable/estimator_overview.html) and [scikit-learn] compatible tools to build, tune and validate time series models.
+sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with [time series algorithms](https://www.sktime.net/en/stable/estimator_overview.html) and [scikit-learn] compatible tools to build, tune and validate time series models.
 
 [scikit-learn]: https://scikit-learn.org/stable/
 
@@ -41,9 +41,9 @@ sktime is a library for time series analysis in Python. It provides a unified in
 [roadmap]: https://www.sktime.net/en/latest/roadmap.html
 [related software]: https://www.sktime.net/en/latest/related_software.html
 
-## :speech_balloon: Where to ask questions
+## :speech_balloon: Where to ask questions!
 
-Questions and feedback are extremely welcome! Please understand that we won't be able to provide individual support via email. We also believe that help is much more valuable if it's shared publicly, so that more people can benefit from it.
+We welcome questions and feedback and appreciate your understanding that we are unable to offer personalized assistance via email. We strongly believe in the value of sharing help publicly, as it allows a wider audience to benefit from it.
 
 | Type                            | Platforms                               |
 | ------------------------------- | --------------------------------------- |
@@ -51,8 +51,8 @@ Questions and feedback are extremely welcome! Please understand that we won't be
 | :sparkles: **Feature Requests & Ideas** | [GitHub Issue Tracker]                       |
 | :woman_technologist: **Usage Questions**          | [GitHub Discussions] · [Stack Overflow] |
 | :speech_balloon: **General Discussion**        | [GitHub Discussions] |
-| :factory: **Contribution & Development** | contributors channel · [Discord] |
-| :globe_with_meridians: **Community collaboration session** | [Discord] - Fridays 3pm UTC, dev/meet-ups channel |
+| :factory: **Contribution & Development** | Contributors channel · [Discord] |
+| :globe_with_meridians: **Community collaboration session** | [Discord] - Fridays 3 pm UTC, dev/meet-ups channel |
 
 [github issue tracker]: https://github.com/sktime/sktime/issues
 [github discussions]: https://github.com/sktime/sktime/discussions
@@ -60,9 +60,9 @@ Questions and feedback are extremely welcome! Please understand that we won't be
 [discord]: https://discord.com/invite/54ACzaFsn7
 
 ## :dizzy: Features
-Our aim is to make the time series analysis ecosystem more interoperable and usable as a whole. sktime provides a __unified interface for distinct but related time series learning tasks__. It features [__dedicated time series algorithms__](https://www.sktime.net/en/stable/estimator_overview.html) and __tools for composite model building__ including pipelining, ensembling, tuning and reduction that enables users to apply an algorithm for one task to another.
+Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a __unified interface for distinct but related time series learning tasks__. It features [__dedicated time series algorithms__](https://www.sktime.net/en/stable/estimator_overview.html) and __tools for composite model building__  such as pipelining, ensembling, tuning, and reduction, empowering users to apply an algorithm designed for one task to another.
 
-sktime also provides **interfaces to related libraries**, for example [scikit-learn], [statsmodels], [tsfresh], [PyOD] and [fbprophet], among others.
+sktime also provides **interfaces to related libraries**, for example [scikit-learn], [statsmodels], [tsfresh], [PyOD], and [fbprophet], among others.
 
 For **deep learning**, see our companion package: [sktime-dl](https://github.com/sktime/sktime-dl).
 
@@ -97,10 +97,10 @@ For **deep learning**, see our companion package: [sktime-dl](https://github.com
 
 
 ## :hourglass_flowing_sand: Install sktime
-For trouble shooting and detailed installation instructions, see the [documentation](https://www.sktime.net/en/latest/installation.html).
+For troubleshooting and detailed installation instructions, see the [documentation](https://www.sktime.net/en/latest/installation.html).
 
 - **Operating system**: macOS X · Linux · Windows 8.1 or higher
-- **Python version**: Python 3.8, 3.9, 3.10, and 3.11 (only 64 bit)
+- **Python version**: Python 3.8, 3.9, 3.10, and 3.11 (only 64-bit)
 - **Package managers**: [pip] · [conda] (via `conda-forge`)
 
 [pip]: https://pip.pypa.io/en/stable/
@@ -136,7 +136,7 @@ conda install -c conda-forge sktime-all-extras
 
 ### Forecasting
 
-```python
+``` python
 from sktime.datasets import load_airline
 from sktime.forecasting.base import ForecastingHorizon
 from sktime.forecasting.model_selection import temporal_train_test_split
@@ -178,7 +178,7 @@ There are many ways to join the sktime community. We follow the [all-contributor
 | -------------------------- | --------------------------------------------------------------        |
 | :gift_heart: **[Contribute]**        | How to contribute to sktime.          |
 | :school_satchel:  **[Mentoring]** | New to open source? Apply to our mentoring program! |
-| :date: **[Meetings]** | Join our discussions, tutorials, workshops and sprints! |
+| :date: **[Meetings]** | Join our discussions, tutorials, workshops, and sprints! |
 | :woman_mechanic:  **[Developer Guides]**      | How to further develop sktime's code base.                             |
 | :construction: **[Enhancement Proposals]** | Design a new feature for sktime. |
 | :medal_sports: **[Contributors]** | A list of all contributors. |
@@ -199,10 +199,10 @@ There are many ways to join the sktime community. We follow the [all-contributor
 
 ## :bulb: Project vision
 
-* **by the community, for the community** -- developed by a friendly and collaborative community.
-* the **right tool for the right task** -- helping users to diagnose their learning problem and suitable scientific model types.
-* **embedded in state-of-art ecosystems** and **provider of interoperable interfaces** -- interoperable with [scikit-learn], [statsmodels], [tsfresh], and other community favourites.
-* **rich model composition and reduction functionality** -- build tuning and feature extraction pipelines, solve forecasting tasks with [scikit-learn] regressors.
-* **clean, descriptive specification syntax** -- based on modern object-oriented design principles for data science.
-* **fair model assessment and benchmarking** -- build your models, inspect your models, check your models, avoid pitfalls.
-* **easily extensible** -- easy extension templates to add your own algorithms compatible with sktime's API.
+* **By the community, for the community** -- developed by a friendly and collaborative community.
+* The **right tool for the right task** -- helping users to diagnose their learning problem and suitable scientific model types.
+* **Embedded in state-of-art ecosystems** and **provider of interoperable interfaces** -- interoperable with [scikit-learn], [statsmodels], [tsfresh], and other community favorites.
+* **Rich model composition and reduction functionality** -- build tuning and feature extraction pipelines, solve forecasting tasks with [scikit-learn] regressors.
+* **Clean, descriptive specification syntax** -- based on modern object-oriented design principles for data science.
+* **Fair model assessment and benchmarking** -- build your models, inspect your models, check your models, and avoid pitfalls.
+* **Easily extensible** -- easy extension templates to add your own algorithms compatible with sktime's API.


Code review comments:
diff_hunk: @@ -41,28 +41,28 @@ sktime is a library for time series analysis in Python. It provides a unified in
 [roadmap]: https://www.sktime.net/en/latest/roadmap.html
 [related software]: https://www.sktime.net/en/latest/related_software.html
 
-## :speech_balloon: Where to ask questions
+## :speech_balloon: Where to ask questions!
 
-Questions and feedback are extremely welcome! Please understand that we won't be able to provide individual support via email. We also believe that help is much more valuable if it's shared publicly, so that more people can benefit from it.
+We welcome questions and feedback and appreciate your understanding that we are unable to offer personalized assistance via email. We strongly believe in the value of sharing help publicly, as it allows a wider audience to benefit from it.
 
 | Type                            | Platforms                               |
 | ------------------------------- | --------------------------------------- |
 | :bug: **Bug Reports**              | [GitHub Issue Tracker]                  |
 | :sparkles: **Feature Requests & Ideas** | [GitHub Issue Tracker]                       |
 | :woman_technologist: **Usage Questions**          | [GitHub Discussions] · [Stack Overflow] |
 | :speech_balloon: **General Discussion**        | [GitHub Discussions] |
-| :factory: **Contribution & Development** | contributors channel · [Discord] |
-| :globe_with_meridians: **Community collaboration session** | [Discord] - Fridays 3pm UTC, dev/meet-ups channel |
+| :factory: **Contribution & Development** | Contributors channel · [Discord] |
path: README.md
text: @user1:
the channel name is actually `dev-chat`, how about saying "`dev-chat` channel"

@author:
 Ya, that sounds great!

diff_hunk: @@ -41,28 +41,28 @@ sktime is a library for time series analysis in Python. It provides a unified in
 [roadmap]: https://www.sktime.net/en/latest/roadmap.html
 [related software]: https://www.sktime.net/en/latest/related_software.html
 
-## :speech_balloon: Where to ask questions
+## :speech_balloon: Where to ask questions!
path: README.md
text: @user1:
I think the "!" doesn't work here

@author:
ok removing that.

diff_hunk: @@ -41,28 +41,28 @@ sktime is a library for time series analysis in Python. It provides a unified in
 [roadmap]: https://www.sktime.net/en/latest/roadmap.html
 [related software]: https://www.sktime.net/en/latest/related_software.html
 
-## :speech_balloon: Where to ask questions
+## :speech_balloon: Where to ask questions!
 
-Questions and feedback are extremely welcome! Please understand that we won't be able to provide individual support via email. We also believe that help is much more valuable if it's shared publicly, so that more people can benefit from it.
+We welcome questions and feedback and appreciate your understanding that we are unable to offer personalized assistance via email. We strongly believe in the value of sharing help publicly, as it allows a wider audience to benefit from it.
path: README.md
text: @user1:
This makes the sentence more negative.

We aren't actually receiving that many emails, how about we just turn this into a neutral: "questions and feedback are extremely welcome!" then just pointing to the table without saying anything about email.

@author:
yes i agree with you.
how about this "We absolutely love hearing your questions and feedback! Just a friendly heads-up, though: we're unable to offer direct support through email. But fear not! We strongly believe that sharing help publicly is the way to go. By doing so, we can ensure that a larger community benefits from the knowledge and assistance provided."

@author:
are you saying that we should remove the part after "questions and feedback are extremely welcome!" ?
sorry if I didn't get you.

@user1:
> are you saying that we should remove the part after "questions and feedback are extremely welcome!" 

Yes, no need to point out the part about email:

* because we actually answer emails (even if pointing to the issue tracker)
* and people don't seem to get the wrong idea that email is the primary route for getting help

So let's just remove it!