update conda dependencies

code/scoring/conda_dependencies.yml

@@ -1,54 +1,36 @@
 # Conda environment specification. The dependencies defined in this file will
-
 # be automatically provisioned for managed runs. These include runs against
-
 # the localdocker, remotedocker, and cluster compute targets.
 
-
 # Note that this file is NOT used to automatically manage dependencies for the
-
 # local compute target. To provision these dependencies locally, run:
-
 # conda env update --file conda_dependencies.yml
 
-
 # Details about the Conda environment file format:
-
 # https://conda.io/docs/using/envs.html#create-environment-file-by-hand
 
-
 # For managing Spark packages and configuration, see spark_dependencies.yml.
-
-
 # Version of this configuration file's structure and semantics in AzureML.
-
 # This directive is stored in a comment to preserve the Conda file structure.
-
 # [AzureMlVersion] = 2
 
-
 name: project_environment
 dependencies:
   # The python interpreter version.
-
   # Currently Azure ML Workbench only supports 3.5.2 and later.
-
-- python=3.6.2
+- python=3.7.5
   # Required by azureml-defaults, installed separately through Conda to
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   # get a prebuilt version and not require build tools for the install.
-
-- psutil=5.3
+- psutil=5.6 #latest
 
 - pip:
     # Required packages for AzureML execution, history, and data preparation.
-  - azureml-sdk[notebooks]    # add the version to lock it ==0.1.74
-  - scipy==1.0.0
+  - azureml-sdk==1.0.72
+  - scipy==1.3.1
   - scikit-learn==0.21.3
-  - pandas==0.23.1
-  - numpy==1.14.5
-  - joblib==0.13.2
-  - gunicorn==19.9.0
+  - pandas==0.25.3
+  - numpy==1.17.3
+  - joblib==0.14.0
+  - gunicorn==19.9.0 
   - flask==1.1.1
-  - azure-ml-api-sdk
-
+