Project Documentation¶

This site provides project documentation. Use the documentation navigation to explore.

How-To Guide¶

Many instructions are common to all our projects.

See ⭐ Workflow: Apply Example to get the example projects running on your machine.

Project Documentation Pages (docs/)¶

• Home - this documentation landing page
• Project Instructions - the standard project workflow
• Your Files - how to copy the example and create your version
• Glossary - project terms and concepts
• API - autogenerated code documentation for the public project interface

Phase 4. Technical Modification¶

Describe your small technical modification to the example project.

Include:

• What you changed
• Why you chose that change
• How you verified that it worked
• What result, output, chart, metric, or behavior confirmed the change

Compared with the example project, explain what is different and why the change matters.

Was it easy, or surprisingly challenging and why do you think so?

Phase 5. Custom Project¶

Describe your custom project and how you made your modeling decisions.

Be specific about what changed from the example project.

Basis and Data¶

Describe the dataset, input, or example you started with.

Include:

• The original example dataset or input
• The data source
• Why you chose it, kept it, or changed it
• Any important limitations or assumptions

Modeling Approach¶

Describe the problem type and modeling approach for this project.

Include:

• Is this supervised or unsupervised and how do you know
• Is this classification, regression, clustering, recommendation, forecasting, or another type of ML task
• What kind of target works well for this approach
• Why your selected model or method is appropriate

Target¶

Describe the example target variable.

Then describe your chosen target variable.

Explain how your target choice changes the modeling approach, interpretation, or evaluation.

Features¶

Describe the example features.

Then describe the features you used to predict your target.

Explain what you changed, added, removed, or kept and why.

Evaluation and Results¶

Describe how you evaluated your model.

Include:

• The metric or evidence you used
• The main result
• Whether the result was useful, interesting, surprising, or disappointing
• Any weakness, limitation, or next improvement

Summary¶

Summarize your custom project.

Include:

• How you implemented your custom model
• What results you got
• What you learned
• How well you exercised the skills covered in this project
• What kinds of real problems you could apply these skills to in the future

Display at least one image or screenshot showing your work.