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machine-learning-library
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
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https://igel.readthedocs.io/en/latest/_sources/readme.rst.txt includes a link to the assets/igel-help.gif, but that path is broken on readthedocs.
readme.rst is included as ../readme.rst in the sphinx build.
The gifs are in asses/igel-help.gif
The sphinx build needs to point to the asset directory, absolutely:
.. image:: /assets/igel-help.gif
I haven't made a patch, because I haven't
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I'm sorry if I missed this functionality, but CLI
version hasn't it for sure (I saw the related code only in generate_code_examples.py
). I guess it will be very useful to eliminate copy-paste phase, especially for large models.
Of course, piping is a solution, but not for development in Jupyter Notebook, for example.
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String representations of dataset objects are used for previewing their contents from the terminal. When converting a Dataset object to a string, we build a table using ascii characters. The current table has fixed width columns that do not take full advantage of the terminal real estate if the dataset only contains a few columns.
echo $dataset;
<img width="574" alt="Annotation
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- Wikipedia
- Wikipedia
What is the desired addition or change?
It would be nice to have some time series methods. Like
Since many time series come in groups it may be useful to think about how the data should be organized to take in many time series and account for seasonality. Also prob