spark-instrumented-optimizer/python/docs/source/reference/ps_ml.rst
Hyukjin Kwon 3d158f9c91 [SPARK-35587][PYTHON][DOCS] Initial porting of Koalas documentation
### What changes were proposed in this pull request?

This PR proposes to port Koalas documentation to PySpark documentation as its initial step.
It ports almost as is except these differences:

- Renamed import from `databricks.koalas` to `pyspark.pandas`.
- Renamed `to_koalas` -> `to_pandas_on_spark`
- Renamed `(Series|DataFrame).koalas` -> `(Series|DataFrame).pandas_on_spark`
- Added a `ps_` prefix in the RST file names of Koalas documentation

Other then that,

- Excluded `python/docs/build/html` in linter
- Fixed GA dependency installataion

### Why are the changes needed?

To document pandas APIs on Spark.

### Does this PR introduce _any_ user-facing change?

Yes, it adds new documentations.

### How was this patch tested?

Manually built the docs and checked the output.

Closes #32726 from HyukjinKwon/SPARK-35587.

Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2021-06-04 11:11:09 +09:00

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.. _api.ml:
==========================
Machine Learning utilities
==========================
.. currentmodule:: pyspark.pandas.mlflow
MLflow
------
Arbitrary MLflow models can be used with Koalas Dataframes,
provided they implement the 'pyfunc' flavor. This is the case
for most frameworks supported by MLflow (scikit-learn, pytorch,
tensorflow, ...). See comprehensive examples in
:func:`load_model` for more information.
.. note::
The MLflow package must be installed in order to use this module.
If MLflow is not installed in your environment already, you
can install it with the following command:
**pip install koalas[mlflow]**
.. autosummary::
:toctree: api/
PythonModelWrapper
load_model