update docs

Author: tswast

bigframes/_config/bigquery_options.py

@@ -161,6 +161,16 @@ def credentials(self, value: Optional[google.auth.credentials.Credentials]):
     def location(self) -> Optional[str]:
         """Default location for job, datasets, and tables.
 
+        >>> import bigframes.pandas as bpd
+        >>> bpd.reset_session()
+        >>> bpd.options.bigquery.location = "us-central1"
+        >>> bpd.options.bigquery.location
+        'us-central1'
+
+        If not set, is set to the location inferred by the first call to
+        func:`bigframes.pandas.read_gbq` or similar. If the location can't be
+        inferred, jobs and temporary data use the US multiregion.
+
         For more information, see https://cloud.google.com/bigquery/docs/locations BigQuery locations.
 
         Returns:

bigframes/ml/__init__.py

@@ -12,19 +12,82 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""BigQuery DataFrames ML provides a SKLearn-like API on the BigQuery engine."""
+"""BigQuery DataFrames ML provides a SKLearn-like API on the BigQuery engine.
+
+.. code:: python
+
+    from bigframes.ml.linear_model import LinearRegression
+    model = LinearRegression()
+    model.fit(feature_columns, label_columns)
+    model.predict(feature_columns_from_test_data)
+
+You can also save your fit parameters to BigQuery for later use.
+
+.. code:: python
+
+    import bigframes.pandas as bpd
+    model.to_gbq(
+        your_model_id,  # For example: "bqml_tutorial.penguins_model"
+        replace=True,
+    )
+    saved_model = bpd.read_gbq_model(your_model_id)
+    saved_model.predict(feature_columns_from_test_data)
+
+See the `BigQuery ML linear regression tutorial
+<https://docs.cloud.google.com/bigquery/docs/linear-regression-tutorial>`_ for a
+detailed example.
+
+See all, the references for ``bigframes.ml`` sub-modules:
+
+* :mod:`bigframes.ml.cluster`
+* :mod:`bigframes.ml.compose`
+* :mod:`bigframes.ml.decomposition`
+* :mod:`bigframes.ml.ensemble`
+* :mod:`bigframes.ml.forecasting`
+* :mod:`bigframes.ml.imported`
+* :mod:`bigframes.ml.impute`
+* :mod:`bigframes.ml.linear_model`
+* :mod:`bigframes.ml.llm`
+* :mod:`bigframes.ml.metrics`
+* :mod:`bigframes.ml.model_selection`
+* :mod:`bigframes.ml.pipeline`
+* :mod:`bigframes.ml.preprocessing`
+* :mod:`bigframes.ml.remote`
+
+Alternatively, check out mod:`bigframes.bigquery.ml` for an interface that is
+more similar to the BigQuery ML SQL syntax.
+"""
+
+from bigframes.ml import (
+    cluster,
+    compose,
+    decomposition,
+    ensemble,
+    forecasting,
+    imported,
+    impute,
+    linear_model,
+    llm,
+    metrics,
+    model_selection,
+    pipeline,
+    preprocessing,
+    remote,
+)
 
 __all__ = [
     "cluster",
     "compose",
     "decomposition",
+    "ensemble",
+    "forecasting",
+    "imported",
+    "impute",
     "linear_model",
+    "llm",
     "metrics",
     "model_selection",
     "pipeline",
     "preprocessing",
-    "llm",
-    "forecasting",
-    "imported",
     "remote",
 ]

docs/reference/index.rst

@@ -10,6 +10,7 @@ packages.
     bigframes._config
     bigframes.bigquery
     bigframes.bigquery.ai
+    bigframes.bigquery.ml
     bigframes.enums
     bigframes.exceptions
     bigframes.geopandas
@@ -26,6 +27,8 @@ scikit-learn.
 .. autosummary::
     :toctree: api
 
+    bigframes.ml
+    bigframes.ml.base
     bigframes.ml.cluster
     bigframes.ml.compose
     bigframes.ml.decomposition
@@ -35,6 +38,7 @@ scikit-learn.
     bigframes.ml.impute
     bigframes.ml.linear_model
     bigframes.ml.llm
+    bigframes.ml.metrics
     bigframes.ml.model_selection
     bigframes.ml.pipeline
     bigframes.ml.preprocessing