Merge pull request #809 from microsoft/staging

Staging to master

.github/ISSUE_TEMPLATE/bug_report.md

@@ -1,8 +1,8 @@
 ---
 name: Bug report
 about: Create a report to help us improve
-title: "[BUG]"
-labels: ''
+title: "[BUG] "
+labels: 'bug'
 assignees: ''
 
 ---

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,8 +1,8 @@
 ---
 name: Feature request
 about: Suggest an idea for this project
-title: "[FEATURE]"
-labels: ''
+title: "[FEATURE] "
+labels: 'enhancement'
 assignees: ''
 
 ---

.github/ISSUE_TEMPLATE/general-ask.md

@@ -1,8 +1,8 @@
 ---
 name: General ask
 about: Technical/non-technical asks about the repo
-title: "[ASK]"
-labels: ''
+title: "[ASK] "
+labels: 'help wanted'
 assignees: ''
 
 ---

.gitignore

@@ -69,6 +69,9 @@ docs/_build/
 # PyBuilder
 target/
 
+# Locust files:
+locustfile.py
+
 # Jupyter Notebook
 .ipynb_checkpoints
 

AUTHORS.md

@@ -2,72 +2,84 @@ Contributors to Recommenders
 ============================
 Recommenders is developed and maintained by a community of people interested in exploring recommendation algorithms and how best to deploy them in industry settings. The goal is to accelerate the workflow of any individual or organization working on recommender systems. Everyone is encouraged to contribute at any level to add and improve the implemented algorithms, notebooks and utilities. 
 
-Core developers (sorted alphabetically)
-----------------------------------
-Core developers are actively supporting the project and have made substantial contributions to the repository.<br>
-They have write access to the repo and provide support reviewing issues and pull requests.
+Maintainers (sorted alphabetically)
+---------------------------------------
+Maintainers are actively supporting the project and have made substantial contributions to the repository.<br>
+They have admin access to the repo and provide support reviewing issues and pull requests.
 
 * **[Andreas Argyriou](https://github.com/anargyri)**
- * SAR single node improvements
- * Reco utils metrics computations
- * Tests for Surprise
-* **[Dan Ciborowski](https://github.com/dciborow)**
- * ALS operationalization notebook
- * SAR PySpark improvement
-* **[Markus Cosowicz](https://github.com/eisber)**
- * SAR improvements on Spark
+ * SAR single node improvements
+ * Reco utils metrics computations
+ * Tests for Surprise
+* **[Jeremy Reynolds](https://github.com/jreynolds01)**
+ * Reference architecture
+* **[Jun Ki Min](https://github.com/loomlike)**
+ * ALS notebook
+ * Wide & Deep algorithm
+* **[Le Zhang](https://github.com/yueguoguo)**
+ * Reco utils
+ * Continuous integration build / test setup
+ * Quickstart, deep dive, algorithm comparison, notebooks
 * **[Miguel González-Fierro](https://github.com/miguelfierro)**
- * Recommendation algorithms review, development and optimization.
- * Reco utils review, development and optimization.
- * Github statistics.
- * Continuous integration build / test setup.
-* **[Scott Graham](https://github.com/gramhagen)**
- * Improving documentation
- * VW notebook
+ * Recommendation algorithms review, development and optimization.
+ * Reco utils review, development and optimization.
+ * Github statistics.
+ * Continuous integration build / test setup.
 * **[Nikhil Joglekar](https://github.com/nikhilrj)**
- * Improving documentation
- * Quick start notebook
- * Operationalization notebook
-* **[Max Kaznady](https://github.com/maxkazmsft)**
- * Early SAR single node code and port from another internal codebase
- * Early SAR on Spark-SQL implementation
- * SAR notebooks
- * SAR unit / integration / smoke tests
- * Early infrastructure design based on collapsing another internal project
-* **[Jianxun Lian](https://github.com/Leavingseason)**
- * xDeepFM algorithm
- * DKN algorithm
-* **[Jun Ki Min](https://github.com/loomlike)**
- * ALS notebook
- * Wide & Deep algorithm
-* **[Jeremy Reynolds](https://github.com/jreynolds01)**
- * Reference architecture
-* **[Mirco Milletarì](https://github.com/WessZumino)**
- * Restricted Boltzmann Machine algorithm
+ * Improving documentation
+ * Quick start notebook
+ * Operationalization notebook
+* **[Scott Graham](https://github.com/gramhagen)**
+ * Improving documentation
+ * VW notebook
 * **[Tao Wu](https://github.com/wutaomsft)**
- * Improving documentation
-* **[Le Zhang](https://github.com/yueguoguo)**
- * Reco utils
- * Continuous integration build / test setup
- * Quickstart, deep dive, algorithm comparison, notebooks
+ * Improving documentation
 
 
-Contributors
-------------
+Contributors (sorted alphabetically)
+-------------------------------------
 [Full List of Contributors](https://github.com/Microsoft/Recommenders/graphs/contributors)
-- To contributors: please add your name to the list when you submit a patch to the project
----
+
+To contributors: please add your name to the list when you submit a patch to the project.
 
 * **[Aaron He](https://github.com/AaronHeee)**
- * Reco utils of NCF.
- * Deep dive notebook demonstrating the use of NCF.
-* **[Nicolas Hug](https://github.com/NicolasHug)**
- * Jupyter notebook demonstrating the use of [Surprise](https://github.com/NicolasHug/Surprise) library for recommendations.
+ * Reco utils of NCF
+ * Deep dive notebook demonstrating the use of NCF
+* **[Bamdev Mishra](https://github.com/bamdevm)**
+ * RLRMC algorithm
+* **[Beth Zeranski](https://github.com/bethz)**
+ * AzureML tests
+* **[Dan Ciborowski](https://github.com/dciborow)**
+ * ALS operationalization notebook
+ * SAR PySpark improvement
 * **[Daniel Schneider](https://github.com/danielsc)**
- * FastAI notebook.
+ * FastAI notebook
+* **[Gianluca Campanella](https://github.com/gcampanella)**
+ * Spark optimization and support
+* **[Heather Spetalnick (Shapiro)](https://github.com/heatherbshapiro)**
+ * AzureML documentation and support
+* **[Jianxun Lian](https://github.com/Leavingseason)**
+ * xDeepFM algorithm
+ * DKN algorithm
+* **[Markus Cosowicz](https://github.com/eisber)**
+ * SAR improvements on Spark
+* **[Max Kaznady](https://github.com/maxkazmsft)**
+ * Early SAR single node code and port from another internal codebase
+ * Early SAR on Spark-SQL implementation
+ * SAR notebooks
+ * SAR unit / integration / smoke tests
+ * Early infrastructure design based on collapsing another internal project
+* **[Mirco Milletarì](https://github.com/WessZumino)**
+ * Restricted Boltzmann Machine algorithm
+* **[Nicolas Hug](https://github.com/NicolasHug)**
+ * Jupyter notebook demonstrating the use of [Surprise](https://github.com/NicolasHug/Surprise) library for recommendations
+* **[Pratik Jawanpuria](https://github.com/pratikjawanpuria)**
+ * RLRMC algorithm
+* **[Robert Alexander](https://github.com/roalexan)**
+ * Windows test pipelines
 * **[Yassine Khelifi](https://github.com/datashinobi)**
-  * SAR notebook quickstart
+ * SAR notebook quickstart
 * **[Zhenhui Xu](https://github.com/motefly)**
-  * Reco utils of LightGBM.
-  * LightGBM notebook quickstart.
+ * Reco utils of LightGBM
+ * LightGBM notebook quickstart