Revise reStructure README document for clarity and consistency by DWNewton · Pull Request #147 · nidhaloff/igel

DWNewton · 2025-06-11T00:12:27Z

Issue #148
Revising documentation for clarity and consistency.

Revisions complete

DWNewton · 2025-06-11T01:30:50Z

docs/README.rst

-    different models and compare their performance in order to find the 'best' one.
-
-
-


This 'Usage' section is already found above at the very beginning of the "Quick Start" section.

DWNewton · 2025-06-11T01:32:42Z

docs/README.rst

+All you need is a **yaml** (or **json**) file, where you describe what you are trying to do. *That's it!*
+
+- *Igel* supports regression, classification and clustering.
+- *Igel* supports auto-ml features like ``ImageClassification`` and ``TextClassification``


Any references to methods, libraries, filenames, folder/directory names, commands, or syntax are displayed as code style.

DWNewton · 2025-06-11T01:36:17Z

docs/README.rst

-I used the famous indian diabetes in this example `indian-diabetes dataset <https://www.kaggle.com/uciml/pima-indians-diabetes-database>`_)
+In the example above, I'm using random forest to classify whether someone has
+diabetes or not depending on significant features in the dataset
+I used the famous `indian-diabetes dataset <https://www.kaggle.com/uciml/pima-indians-diabetes-database>` in this example


Streamlined the link

DWNewton · 2025-06-11T01:41:30Z

docs/README.rst

-    igel uses pandas under the hood to read & parse the data. Hence, you can
-    find this data optional parameters also in the pandas official documentation.
+    *igel* uses ``pandas`` under the hood to read & parse the data. Hence, you can
+    find optional read parameters within ``pandas`` `official documentation<https://pandas.pydata.org/docs/user_guide/io.html>`.


Added convenience link to pandas documentation pages

DWNewton · 2025-06-11T01:42:18Z

docs/README.rst

+- *Igel* supports auto-ml features like ``ImageClassification`` and ``TextClassification``
+- *Igel* supports most dataset types used in the data science field. For instance, your input dataset can be
+a ``csv``, ``txt``, excel sheet, ``json`` or even ``html`` file that you want to fetch. If using auto-ml features, you can even
+feed raw data to *igel* and it will figure out how to deal with it. See the :ref:`examples<Examples>` for how this works.


Internal document reference to the Examples section for quick navigation

DWNewton · 2025-06-11T01:43:54Z

docs/README.rst

+You can also carry out some preprocessing methods or other operations by providing them in the ``yaml`` file.
 Here is an example, where the data is split to 80% for training and 20% for validation/testing.
-Also, the data are shuffled while splitting.
+(A split of 0.2 means that 20% of the data will be used for testing and 80% for training).


Clarified so users/readers have a better understanding of what the parameters in the code actually mean.

DWNewton · 2025-06-11T01:44:52Z

docs/README.rst

+The data points are shuffled while splitting.

-Furthermore, the data are preprocessed by replacing missing values with the mean ( you can also use median, mode etc..).
+Furthermore, the data are preprocessed by interpolating missing values with the mean ( you can also use median, mode etc..).


Corrected term to that used in the field.

DWNewton · 2025-06-11T01:45:54Z

docs/README.rst


- folder 0, which contains cats images (here the label 0 indicates a cat)
- folder 1, which contains dogs images (here the label 1 indicates a dog)
+| images/


Provided visual depiction of proper folder/file structure for dataset

DWNewton · 2025-06-11T01:47:06Z

docs/README.rst

-You can also run the igel UI if you are not familiar with the terminal. Just install igel on your machine
-as mentioned above. Then run this single command in your terminal
+You can also run the *igel* UI if you are not familiar with terminal commands. Just install *igel* on your machine
+as :ref:`mentioned above<Installation>`. Then run this simple, single command in your terminal:


Internal document reference linking to installation steps for convenience

DWNewton · 2025-06-11T01:47:46Z

docs/README.rst

-This will open up the gui, which is very simple to use. Check examples of how the gui looks like and how to use it
-here: https://github.com/nidhaloff/igel-ui
+This opens up the gui, which is very easy to use. Check examples of how the gui looks and how to use it
+here: `https://github.com/nidhaloff/igel-ui<https://github.com/nidhaloff/igel-ui>`_.


RST document formatted URL

DWNewton · 2025-06-11T01:48:34Z

docs/README.rst


- Article: https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890
-
+- Article: `https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890<https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890>`_


RST format URL

DWNewton · 2025-06-11T01:49:05Z

docs/README.rst

+Do you like *igel*?
 You can always help the development of this project by:

 - Following on github and/or twitter


Do we want to put links for any of these within the document?

DWNewton · 2025-06-11T01:50:35Z

docs/README.rst

-I needed a tool sometimes, which I can use to fast create a machine learning prototype. Whether to build
-some proof of concept, create a fast draft model to prove a point or use auto ML. I find myself often stuck at writing
-boilerplate code and thinking too much where to start. Therefore, I decided to create this tool.
+* **If you** are a non-technical person who wants to use machine learning, but you don't know how to code or you don't want to write code,


Added/Revised order of these paragraphs for better flow and clarity

DWNewton added 2 commits June 10, 2025 20:11

Initial docs/README.rst revisions

2668f3d

Finished 'docs/README.rst' revisions

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DWNewton commented Jun 11, 2025

View reviewed changes

Added additional codeblock formatting

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DWNewton commented Jun 11, 2025

View reviewed changes

DWNewton added 2 commits June 10, 2025 21:51

Fixed formatting errors I missed

6920655

Additional clarification and formatting

dd7b507

DWNewton mentioned this pull request Jun 11, 2025

Revise reStructure README.rst document #148

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		different models and compare their performance in order to find the 'best' one.


		- Article: https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890

		- Article: `https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890<https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890>`_

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DWNewton commented Jun 11, 2025 •

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