Create release notes for version 1.3.0.

docs/release-notes/release-1.3.0.md

@@ -0,0 +1,94 @@
+# [NimbusML](https://docs.microsoft.com/en-us/nimbusml/overview) 1.3.0
+
+## **New Features**
+
+- **Save/Restore model when pickling Pipeline**
+
+   [PR#189](https://github.com/microsoft/NimbusML/pull/189) Save and restore
+   the underlying model file when pickling a nimbusml Pipeline.
+
+- **Feature Contributions**
+
+  [PR#196](https://github.com/microsoft/NimbusML/pull/196) Added support for
+  observation level feature contributions. Exposes an API
+  `Pipeline.get_feature_contributions()` that provides scores for how much
+  each feature influenced a particular prediction, thereby allowing users to
+  inspect which features were most important in making the prediction.
+
+- **Add `classes_` to Pipeline**
+
+   [PR#200](https://github.com/microsoft/NimbusML/pull/200) Add a `classes_`
+   attribute to a Pipeline and/or predictor instance when calling
+   `Pipeline.predict_proba()`.
+
+- **Automatically Convert Input Of Handler, Filter and Indicator**
+
+   [PR#204](https://github.com/microsoft/NimbusML/pull/204) Update Handler,
+   Filter, and Indicator to automatically convert the input columns to float
+   before performing the transform.
+
+- **Combine Models**
+
+   [PR#208](https://github.com/microsoft/NimbusML/pull/208) Add support for
+   combining models from transforms, predictors and pipelines in to one model.
+
+- **Azureml-Dataprep integration**
+
+   [PR#181](https://github.com/microsoft/NimbusML/pull/181) Added support for
+   dataflow objects as a datasource for pipeline training/testing.
+
+- **Linear SVM Binary Classifier**
+  [PR#180](https://github.com/microsoft/NimbusML/pull/180) Added
+  `LinearSvmBinaryClassifier` in `nimbusml.linear_model`.
+
+- **Ensemble Training**
+
+  [PR#207](https://github.com/microsoft/NimbusML/pull/207) Enabled training of
+  Ensemble models by adding `nimbusml.ensemble.EnsembleRegressor` and 
+  `nimbusml.ensemble.EnsembleClassifier`. Added components needed
+  to create ensemble models as new modules in `nimbusml.ensemble`. These
+  components are passed as arguments to the ensemble trainers.
+  - Preprocessing components for training multiple models to ensemble in 
+  `nimbusml.ensemble.subset_selector` and  `nimbusml.ensemble.feature_selector`.
+  - Post training components to create the ensemble from the trained models in
+  `nimbusml.ensemble.sub_model_selector` and `nimbusml.ensemble.output_combiner`.
+
+## **Bug Fixes**
+
+- **Fixed memory leak**
+
+   The [PR#184](https://github.com/microsoft/NimbusML/pull/184) fixed potentially
+   large memory leak when transforming pandas dataframe.
+
+- **Remove Stored References To `X` and `y`**
+
+   [PR#195](https://github.com/microsoft/NimbusML/pull/195) Remove the stored
+   references to X and y in BasePredictor.
+
+- **Fixed Explicit `evaltype`**
+
+   The [issue](https://github.com/microsoft/NimbusML/issues/193) where passing
+   in an explicit `evaltype` to `_predict` in a NimbusML pipeline causes errors
+   has been fixed with this
+   [commit](https://github.com/microsoft/NimbusML/commit/1f97c9ef55f5e257f989db5f375cca5c55880258).
+
+## **Breaking Changes**
+
+None.
+
+## **Enhancements**
+
+None.
+
+## **Documentation and Samples**
+
+[Feature Contributions Example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/PipelineWithFeatureContributions.py)
+
+LinearSvmBinaryClassifier Examples:
+- [FileDataStream example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py)
+- [DataFrame example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/examples_from_dataframe/LinearSvmBinaryClassifier_df.py)
+
+
+## **Remarks**
+
+None.

release-next.md

@@ -2,75 +2,11 @@
 
 ## **New Features**
 
-- **Save/Restore model when pickling Pipeline**
-
-   [PR#189](https://github.com/microsoft/NimbusML/pull/189) Save and restore
-   the underlying model file when pickling a nimbusml Pipeline.
-
-- **Feature Contributions**
-
-  [PR#196](https://github.com/microsoft/NimbusML/pull/196) Added support for
-  observation level feature contributions. Exposes an API
-  `Pipeline.get_feature_contributions()` that provides scores for how much
-  each feature influenced a particular prediction, thereby allowing users to
-  inspect which features were most important in making the prediction.
-
-- **Add `classes_` to Pipeline**
-
-   [PR#200](https://github.com/microsoft/NimbusML/pull/200) Add a `classes_`
-   attribute to a Pipeline and/or predictor instance when calling
-   `Pipeline.predict_proba()`.
-
-- **Automatically Convert Input Of Handler, Filter and Indicator**
-
-   [PR#204](https://github.com/microsoft/NimbusML/pull/204) Update Handler,
-   Filter, and Indicator to automatically convert the input columns to float
-   before performing the transform.
-
-- **Combine Models**
-
-   [PR#208](https://github.com/microsoft/NimbusML/pull/208) Add support for
-   combining models from transforms, predictors and pipelines in to one model.
-
-- **Azureml-Dataprep integration**
-
-   [PR#181](https://github.com/microsoft/NimbusML/pull/181) Added support for
-   dataflow objects as a datasource for pipeline training/testing.
-
-- **Linear SVM Binary Classifier**
-  [PR#180](https://github.com/microsoft/NimbusML/pull/180) Added
-  `LinearSvmBinaryClassifier` in `nimbusml.linear_model`.
-
-- **Ensemble Training**
-
-  [PR#207](https://github.com/microsoft/NimbusML/pull/207) Enabled training of
-  Ensemble models by adding `nimbusml.ensemble.EnsembleRegressor` and 
-  `nimbusml.ensemble.EnsembleClassifier`. Added components needed
-  to create ensemble models as new modules in `nimbusml.ensemble`. These
-  components are passed as arguments to the ensemble trainers.
-  - Preprocessing components for training multiple models to ensemble in 
-  `nimbusml.ensemble.subset_selector` and  `nimbusml.ensemble.feature_selector`.
-  - Post training components to create the ensemble from the trained models in
-  `nimbusml.ensemble.sub_model_selector` and `nimbusml.ensemble.output_combiner`.
+None.
 
 ## **Bug Fixes**
 
-- **Fixed memory leak**
-
-   The [PR#184](https://github.com/microsoft/NimbusML/pull/184) fixed potentially
-   large memory leak when transforming pandas dataframe.
-
-- **Remove Stored References To `X` and `y`**
-
-   [PR#195](https://github.com/microsoft/NimbusML/pull/195) Remove the stored
-   references to X and y in BasePredictor.
-
-- **Fixed Explicit `evaltype`**
-
-   The [issue](https://github.com/microsoft/NimbusML/issues/193) where passing
-   in an explicit `evaltype` to `_predict` in a NimbusML pipeline causes errors
-   has been fixed with this
-   [commit](https://github.com/microsoft/NimbusML/commit/1f97c9ef55f5e257f989db5f375cca5c55880258).
+None.
 
 ## **Breaking Changes**
 
@@ -82,12 +18,7 @@ None.
 
 ## **Documentation and Samples**
 
-[Feature Contributions Example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/PipelineWithFeatureContributions.py)
-
-LinearSvmBinaryClassifier Examples:
-- [FileDataStream example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py)
-- [DataFrame example](https://github.com/microsoft/NimbusML/blob/master/src/python/nimbusml/examples/examples_from_dataframe/LinearSvmBinaryClassifier_df.py)
-
+None. 
 
 ## **Remarks**