Revise reStructure README document for clarity and consistency #147
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DWNewton
commented
Jun 11, 2025
| different models and compare their performance in order to find the 'best' one. | ||
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This 'Usage' section is already found above at the very beginning of the "Quick Start" section.
DWNewton
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Jun 11, 2025
| All you need is a **yaml** (or **json**) file, where you describe what you are trying to do. *That's it!* | ||
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| - *Igel* supports regression, classification and clustering. | ||
| - *Igel* supports auto-ml features like ``ImageClassification`` and ``TextClassification`` |
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Any references to methods, libraries, filenames, folder/directory names, commands, or syntax are displayed as code style.
DWNewton
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Jun 11, 2025
docs/README.rst
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| 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 |
DWNewton
commented
Jun 11, 2025
| 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>`. |
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Added convenience link to pandas documentation pages
DWNewton
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Jun 11, 2025
docs/README.rst
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| - *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. |
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Internal document reference to the Examples section for quick navigation
DWNewton
commented
Jun 11, 2025
| 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). |
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Clarified so users/readers have a better understanding of what the parameters in the code actually mean.
DWNewton
commented
Jun 11, 2025
| The data points are shuffled while splitting. | ||
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| 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..). |
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Corrected term to that used in the field.
DWNewton
commented
Jun 11, 2025
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| - 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/ |
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Provided visual depiction of proper folder/file structure for dataset
DWNewton
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Jun 11, 2025
| 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: |
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Internal document reference linking to installation steps for convenience
DWNewton
commented
Jun 11, 2025
| 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>`_. |
DWNewton
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Jun 11, 2025
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| - Article: https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890 | ||
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| - Article: `https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890<https://medium.com/@nidhalbacc/machine-learning-without-writing-code-984b238dd890>`_ |
DWNewton
commented
Jun 11, 2025
| Do you like *igel*? | ||
| You can always help the development of this project by: | ||
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| - Following on github and/or twitter |
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Do we want to put links for any of these within the document?
DWNewton
commented
Jun 11, 2025
| 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, |
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Added/Revised order of these paragraphs for better flow and clarity
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Issue #148
Revising documentation for clarity and consistency.