setup.md

title
Setup scikit-learn kernel in Palmetto's JupyterLab

We will use Palmetto cluster for this workshop with Jupyter Lab.

Please follow this guideline to create a new conda environment and install scikit-learn package. Log into Clemson's OpenOnDemand

Under Clusters select Palmetto Shell Access

Log into the Palmetto Command Line Shell

Run the following qsub command

$ qsub -I -l select=1:ncpus=8:mem=15gb:interconnect=1g,walltime=24:00:00

Next, run the following commands.

$ module load anaconda3/2021.05-gcc/8.3.1
$ conda create -n skln python=3.8 -y
$ source activate skln
$ conda install numpy pandas scikit-learn seaborn matplotlib jupyterlab -y

=> Note: while using skln conda environment, if we are missing anything, we can always come back and update using pip install or conda install method.

Go back to OpenOnDemand Dashboard, under Interactive Apps select Jupyter Notebook

Make the selection on the Jupyter Notebook App as follows:

• Anaconda Version: anaconda3/2021.05-gcc/8.3.1
• Path to Python virtual/conda environment: source activate skln
• Notebook Workflow: Standard Jupyter Notebook
• Number of resource chunks (select): 1
• CPU cores per chunk (ncpus): 8
• Amount of memory per chunk (mem): 15gb
• Interconnect: 1g - Ethernet older phases 1-6
• Walltime: 04:00:00

Click Launch.

Click Connect to Jupyter once the job is ready.

Open a new notebook using the default Python 3 kernel. Test for the valid installation of scikit-learn.

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