Workshop 2: Machine Learning in Forest Modeling

Welcome to this workshop’s repository. Here you’ll find the code tutorials we will run during the workshop.

To get started, clone this repository to your local workstation. You can do that with the following:

git clone https://github.com/ttrotto/EDI-HPC.git

The python folder contains the code for the unsupervised learning and distributed computing tutorials. For the Python tutorials, the html folder contains the rendered markdowns for easier readability.

Python

Next, for Python users you should be able to prepare an environment to install the dependencies in requirements.txt. You can do that with pip:

Linux

# create virtual environment
python3 -m venv .venv
source .venv/bin/activate

# install pip
python3 -m pip install --upgrade pip

# install dependencies
python3 -m pip install -r requirements.txt

Windows

# create virtual environment
py -m venv .venv
.venv\Scripts\activate

# install pip
py -m pip install --upgrade pip

# install dependencies
py -m pip install -r requirements.txt

Note that we do not provide dependencies for the tutorial on distributed workloads as many don’t have access to HPC clusters. In case you do, you can also install dask, dask-ml, and dask-jobqueue

Have fun coding!