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Session 5 Tutorial
Distributed Machine Learning: Using Gradient Boosting to Predict NDVI Dynamics
This page contains all the info you need to participate in Session 5 of the SCINet Geospatial Workshop 2020.
A note about running this tutorial in your home directory: some participants got errors either downloading to or running the tutorial from their home directory because they did not have enough space free in their home directory. If this happens to you, download to and run the tutorial from a project directory. If you are a new HPC user and don’t yet have a project directory, you can request a small increase in space to your home directory from the SCINet VRSC at scinet_vrsc@usda.gov.
The session recording is available for anyone with a usda.gov email address and eAuthentication at (location coming soon).
Learning Goals
- introduction to a preprocessing data pipeline for machine learning
- understand challenges and a set of solutions to distributed computing (via dask distributed) with machine learning
- run a distrubted machine learning workflow (hyperparameter tuning, training, validation, and model interpretation)
Contents
How to Run the Tutorial on Ceres
Session Rules
GREEN LIGHT, RED LIGHT - Use the Zoom participant feedback indicators to show us if you are following along successfully as well as when you need help. To access participant feed back, click on the “Participants” icon to open the participants pane/window. Click the green “yes” to indicate that you are following along successfully, click the red “no” to indicate when you need help. Ideally, you will have either the red or green indicator displayed for yourself throughout the entire tutorial. We will pause every so often to work through solutions for participants displaying a red light.
CHAT QUESTIONS/COMMENTS TAKE FIRST PRIORITY - Chat your questions/comments either to everyone (preferred) or to the chat moderator (Rowan Gaffney) privately to have your question/comment read out loud anonamously. We will address chat questions/comments first and call on people who have written in the chat before we take questions from raised hands.
SHARE YOUR VIDEO WHEN SPEAKING - If your internet plan/connectivity allows, please share your video when speaking.
KEEP YOURSELF ON MUTE - Please mute yourself unless you are called on.
How to Run the Tutorial on Ceres
Step 1: Login to your SCINet/Ceres account through the JupyterHub web interface
- Go to https://jupyterhub.scinet.usda.gov
- Login to the system with your SCINet credentials
- Submit the Spawning Page with the following information (if not specified below, leave blank):
Node Type:short
Number of Cores:4
Job Duration:02:00:00
These next two fields are important to enter correctly on the Spawning Page or you will not be able to run the tutorials once you are logged in. Please use copy/paste to avoid mistakes instead of typing these lines:
Path to the container image: /lustre/project/geospatial_tutorials/wg_2020_ws/data_science_im_rs_vSCINetGeoWS_2020.sif
Container Exec Args: --bind /etc/munge --bind /var/log/munge --bind /var/run/munge --bind /usr/bin/squeue --bind /usr/bin/scancel --bind /usr/bin/sbatch --bind /usr/bin/scontrol --bind /usr/bin/sinfo --bind /system/slurm:/etc/slurm --bind /run/munge --bind /usr/lib64/libslurm.so --bind /usr/lib64/libmunge.so.2 --bind /usr/lib64/slurm --bind /project --bind /lustre
After a few minutes, a JupyterLab instance running on the Ceres HPC should open in your browser. After several attempts, if the spawner fails and JupyterLab does not open correctly, please contact the SCINet Virtual Research Support Core (VRSC) for assistance at scinet_vrsc@usda.gov.
Step 2: Copy the tutorial jupyter notebook file into your home directory
From inside JupyterLab File > New > Terminal to open a terminal tab.
At the command line
cp /project/shared_files/GEOSPATIAL_WORKSHOP/session5_machine_learning.ipynb .
Note: The original method listed here for accessing our tutorials (from GitHub) was not working for some participants in Session 3. It will be easiest to copy the files from the shared folder on Ceres as above… but an alternate method you can try is to download the tutorial material from the workshop GitHub repo.
- Open a terminal: File–>New–>terminal (alternatively, click the “+” icon (launcher) on the left and then choose the “terminal” icon on the launcher screen)
- Download the tutorials to your home directory
git clone --single-branch https://github.com/kerriegeil/SCINET-GEOSPATIAL-RESEARCH-WG.git
Step 3: Run a notebook
- You should now see the file session5_machine_learning.ipynb (in the file system extension on the left hand side of JupyterLab, you may have to click the refresh icon in JupyterLab)
- Double click the session5 file to open it
- Select the py_geo kernel (upper right corner in the notebook)
-
Execute blocks of script by clicking the “play” icon in the notebook or typing Shift+Enter
- If you used git clone to get the tutorial Navigate to ~/SCINET-GEOSPATIAL-RESEARCH-WG/tutorials/session5_machine_learning.ipynb
View the Tutorial Online
If you are not running the tutorial on Ceres during the session you can view a static version of it at https://kerriegeil.github.io/SCINET-GEOSPATIAL-RESEARCH-WG/html-tutorials/session5_machine_learning.html