update samples from Release-88 as a part of 1.29.0 SDK stable release

2021-05-24 17:04:07 +00:00
2 changed files with 4 additions and 2 deletions
--- a/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb
+++ b/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb
@@ -184,10 +184,12 @@
        "\n",
        "env = Environment(name=\"mlflow-env\")\n",
        "\n",
+        "env.docker.enabled = True\n",
+        "\n",
        "# Specify conda dependencies with scikit-learn and temporary pointers to mlflow extensions\n",
        "cd = CondaDependencies.create(\n",
        "    conda_packages=[\"scikit-learn\", \"matplotlib\"],\n",
-        "    pip_packages=[\"azureml-mlflow\", \"pandas\", \"numpy\"]\n",
+        "    pip_packages=[\"azureml-mlflow\", \"numpy\"]\n",
        "    )\n",
        "\n",
        "env.python.conda_dependencies = cd"
--- a/how-to-use-azureml/work-with-data/datasets-tutorial/pipeline-with-datasets/pipeline-for-image-classification.ipynb
+++ b/how-to-use-azureml/work-with-data/datasets-tutorial/pipeline-with-datasets/pipeline-for-image-classification.ipynb
@@ -274,7 +274,7 @@
        "- pip:\n",
        "  - azureml-defaults\n",
        "  - keras\n",
-        "  - tensorflow<=2.4.*\n",
+        "  - tensorflow\n",
        "  - numpy\n",
        "  - scikit-learn\n",
        "  - pandas\n",