Replacing the model for deployment to the endpoint

Labs/02/Run training script.ipynb

@@ -143,7 +143,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python diabetes-training.py\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-pythonv2-train\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/03/Work with data.ipynb

@@ -664,7 +664,7 @@
         "    command=\"python move-data.py --input_data ${{inputs.local_data}} --output_datastore ${{outputs.datastore_data}}\",\n",
         "    inputs=my_job_inputs,\n",
         "    outputs=my_job_outputs,\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"move-diabetes-data\",\n",
         "    experiment_name=\"move-diabetes-data\"\n",

Labs/04/Work with compute.ipynb

@@ -355,7 +355,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python diabetes-training.py\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-cluster\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/04/Work with environments.ipynb

@@ -175,7 +175,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python diabetes-training.py\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-curated-env\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/08/Run script as a command job.ipynb

@@ -117,7 +117,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-parameters.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-script\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/08/Use MLflow to track jobs.ipynb

@@ -264,7 +264,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-mlflow.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-mlflow\",\n",
         "    experiment_name=\"diabetes-training\", \n",
@@ -450,7 +450,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-autolog.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-autolog\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/09/Hyperparameter tuning.ipynb

@@ -300,7 +300,7 @@
         "            ),\n",
         "        \"reg_rate\": 0.01,\n",
         "    },\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-mlflow\",\n",
         "    experiment_name=\"diabetes-training\", \n",

Labs/09/Run a pipeline job.ipynb

@@ -359,7 +359,7 @@
     "  output_data:\n",
     "    type: uri_folder\n",
     "code: ./src\n",
-    "environment: azureml:AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\n",
+    "environment: azureml:AzureML-sklearn-1.5@latest\n",
     "command: >-\n",
     "  python prep-data.py \n",
     "  --input_data ${{inputs.input_data}}\n",
@@ -392,7 +392,7 @@
     "  model_output:\n",
     "    type: mlflow_model\n",
     "code: ./src\n",
-    "environment: azureml:AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\n",
+    "environment: azureml:AzureML-sklearn-1.5@latest\n",
     "command: >-\n",
     "  python train-model.py \n",
     "  --training_data ${{inputs.training_data}} \n",

Labs/10/Log models with MLflow.ipynb

@@ -239,7 +239,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-autolog.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-autolog\",\n",
         "    experiment_name=\"diabetes-training\"\n",
@@ -416,7 +416,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-sklearn.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-sklearn\",\n",
         "    experiment_name=\"diabetes-training\"\n",
@@ -586,7 +586,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-infer.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-infer\",\n",
         "    experiment_name=\"diabetes-training\"\n",
@@ -772,7 +772,7 @@
         "job = command(\n",
         "    code=\"./src\",\n",
         "    command=\"python train-model-signature.py --training_data diabetes.csv\",\n",
-        "    environment=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu@latest\",\n",
+        "    environment=\"AzureML-sklearn-1.5@latest\",\n",
         "    compute=\"aml-cluster\",\n",
         "    display_name=\"diabetes-train-signature\",\n",
         "    experiment_name=\"diabetes-training\"\n",

Labs/10/model/MLmodel

@@ -1,25 +1,27 @@
 artifact_path: model
 flavors:
   python_function:
-    env: conda.yaml
+    env:
+      conda: conda.yaml
+      virtualenv: python_env.yaml
     loader_module: mlflow.sklearn
     model_path: model.pkl
     predict_fn: predict
-    python_version: 3.7.15
+    python_version: 3.10.19
   sklearn:
     code: null
     pickled_model: model.pkl
     serialization_format: cloudpickle
-    sklearn_version: 0.24.1
-mlflow_version: 1.30.0
-model_uuid: 580862f780fb48eda0a137857d12c9f9
-run_id: calm_garden_gzd94mfzcr
+    sklearn_version: 1.5.2
+mlflow_version: 2.22.2
+model_size_bytes: 782
+model_uuid: 746375f7efea49bcb7afa81380e80395
+run_id: teal_answer_v5t7yq9zwn
 signature:
-  inputs: '[{"name": "PatientID", "type": "integer"}, {"name": "Pregnancies", "type":
-    "integer"}, {"name": "PlasmaGlucose", "type": "integer"}, {"name": "DiastolicBloodPressure",
-    "type": "integer"}, {"name": "TricepsThickness", "type": "integer"}, {"name":
-    "DiastolicBloodPressure", "type": "integer"}, {"name": "SerumInsulin", "type":
-    "integer"}, {"name": "BMI", "type": "double"}, {"name": "DiabetesPedigree", "type":
-    "double"}, {"name": "Age", "type": "integer"}]'
-  outputs: '[{"type": "boolean"}]'
-utc_time_created: '2023-02-15 12:46:19.119720'
+  inputs: '[{"name": "Pregnancies", "type": "double"}, {"name": "PlasmaGlucose", "type": "double"},
+    {"name": "DiastolicBloodPressure", "type": "double"}, {"name": "TricepsThickness", "type": "double"}, {"name":
+    "SerumInsulin", "type": "double"}, {"name": "BMI", "type": "double"}, {"name": "DiabetesPedigree", "type":
+    "double"}, {"name": "Age", "type": "double"}]'
+  outputs: '[{"type": "double"}]'
+type_hint_from_example: false
+utc_time_created: '2025-12-11 03:22:29.198079'

Labs/10/model/conda.yaml

@@ -1,11 +1,15 @@
 channels:
 - conda-forge
 dependencies:
-- python=3.7.15
-- pip<=20.2.4
+- python=3.10.19
+- pip<=25.3
 - pip:
-  - mlflow
-  - cloudpickle==2.2.0
+  - mlflow==2.22.2
+  - backports-tempfile==1.0
+  - cloudpickle==2.2.1
+  - jaraco-collections==5.1.0
+  - numpy==1.22.4
+  - pandas==1.5.3
   - psutil==5.8.0
-  - scikit-learn==0.24.1
+  - scikit-learn==1.5.2
 name: mlflow-env

Labs/10/model/python_env.yaml

@@ -1,7 +1,7 @@
-python: 3.7.15
+python: 3.10.19
 build_dependencies:
-- pip==20.2.4
-- setuptools==65.6.3
-- wheel==0.37.1
+- pip==25.3
+- setuptools==80.9.0
+- wheel==0.45.1
 dependencies:
 - -r requirements.txt

Labs/10/model/requirements.txt

@@ -1,4 +1,8 @@
-mlflow
-cloudpickle==2.2.0
+mlflow==2.22.2
+backports-tempfile==1.0
+cloudpickle==2.2.1
+jaraco-collections==5.1.0
+numpy==1.22.4
+pandas==1.5.3
 psutil==5.8.0
-scikit-learn==0.24.1
+scikit-learn==1.5.2

Labs/11/Deploy to batch endpoint.ipynb

@@ -257,10 +257,10 @@
       },
       "outputs": [],
       "source": [
-        "from azure.ai.ml.entities import BatchDeployment, BatchRetrySettings\n",
+        "from azure.ai.ml.entities import ModelBatchDeployment, BatchRetrySettings\n",
         "from azure.ai.ml.constants import BatchDeploymentOutputAction\n",
         "\n",
-        "deployment = BatchDeployment(\n",
+        "deployment = ModelBatchDeployment(\n",
         "    name=\"classifier-diabetes-mlflow\",\n",
         "    description=\"A diabetes classifier\",\n",
         "    endpoint_name=endpoint.name,\n",

Labs/11/model/MLmodel

@@ -1,21 +1,27 @@
 artifact_path: model
 flavors:
   python_function:
-    env: conda.yaml
+    env:
+      conda: conda.yaml
+      virtualenv: python_env.yaml
     loader_module: mlflow.sklearn
     model_path: model.pkl
-    python_version: 3.8.17
+    predict_fn: predict
+    python_version: 3.10.19
   sklearn:
+    code: null
     pickled_model: model.pkl
     serialization_format: cloudpickle
-    sklearn_version: 1.3.0
-mlflow_version: 1.30.0
-model_uuid: ba8abd76e4cb479a81145f1bb76472e4
-run_id: 36b85079-2e17-43da-b4b4-775944b9a2d3
+    sklearn_version: 1.5.2
+mlflow_version: 2.22.2
+model_size_bytes: 782
+model_uuid: 746375f7efea49bcb7afa81380e80395
+run_id: teal_answer_v5t7yq9zwn
 signature:
   inputs: '[{"name": "Pregnancies", "type": "double"}, {"name": "PlasmaGlucose", "type": "double"},
     {"name": "DiastolicBloodPressure", "type": "double"}, {"name": "TricepsThickness", "type": "double"}, {"name":
     "SerumInsulin", "type": "double"}, {"name": "BMI", "type": "double"}, {"name": "DiabetesPedigree", "type":
     "double"}, {"name": "Age", "type": "double"}]'
   outputs: '[{"type": "double"}]'
-utc_time_created: '2022-11-01 20:46:17.296023'
+type_hint_from_example: false
+utc_time_created: '2025-12-11 03:22:29.198079'

Labs/11/model/conda.yaml

@@ -1,11 +1,15 @@
 channels:
 - conda-forge
 dependencies:
-- python=3.8.17
-- pip<=20.2.4
+- python=3.10.19
+- pip<=25.3
 - pip:
-  - mlflow
+  - mlflow==2.22.2
+  - backports-tempfile==1.0
   - cloudpickle==2.2.1
-  - psutil==5.9.5
-  - scikit-learn==1.3.0
+  - jaraco-collections==5.1.0
+  - numpy==1.22.4
+  - pandas==1.5.3
+  - psutil==5.8.0
+  - scikit-learn==1.5.2
 name: mlflow-env

Labs/11/model/python_env.yaml

@@ -1,7 +1,7 @@
-python: 3.8.17
+python: 3.10.19
 build_dependencies:
-- pip==20.2.4
-- setuptools==65.5.0
-- wheel==0.37.1
+- pip==25.3
+- setuptools==80.9.0
+- wheel==0.45.1
 dependencies:
 - -r requirements.txt

Labs/11/model/requirements.txt

@@ -1,4 +1,8 @@
-mlflow
+mlflow==2.22.2
+backports-tempfile==1.0
 cloudpickle==2.2.1
-psutil==5.9.5
-scikit-learn==1.3.0
+jaraco-collections==5.1.0
+numpy==1.22.4
+pandas==1.5.3
+psutil==5.8.0
+scikit-learn==1.5.2