ML Workbench for an Existing Jupyter Server
If you have a running Jupyter lab server or you are using the Jupyter lab on Microsoft Azure, AWS Sagemaker, or Google Vertex AI, you can still take advantage of our ML Workbench by installing the Python package.
You can choose to install on the base kernel or using a Conda environment.
From JupyterLab, open a new terminal and run the following command to install pyTigerGraph:
pip install pyTigerGraph[gds]
Run the following command to install our Python environment:
source activate tigergraph-torch-cpuor
source activate tigergraph-torch-gputo activate your environment depending on if you installed a CPU or GPU environment.
Run the following command to install the Python kernel: