Getting Started with Python
This baseline project shows how to get the most out of Python on Cloudera Data Science Workbench.
Files
Modify the default files to get started with your own project.
README.md
-- This project's readme in Markdown format.analysis.py
-- An example Python analysis script.cdsw-build.sh
-- A custom build script used for models and experiments. This will pip install our dependencies, primarily the scikit-learn library.fit.py
-- A model training example to be run as an experiment. Generates the model.pkl file that contains the fitted parameters of our model.predict.py
-- A sample function to be deployed as a model. Usesmodel.pkl
produced byfit.py
to make predictions about petal width.
Instructions for Sessions
- Click "Open Workbench".
- Launch a new Python session.
- Run
analysis.py
in the workbench.
Instructions for Experiments and Models
- Click "Open Workbench".
- Run an experiment with
fit.py
as the input script. - Once the experiment is complete, save the
model.pkl
file to the project. - Deploy a model using
predict.py
. Specifypredict
as the input function.
For detailed instructions on how to run these scripts, see the documentation.