Exploratory Data Analysis templates

Helps you understand the data you are working with before modeling

• Data overview
  • Sample rows
  • Missing values
  • Unique values
• Statistical overview
  • Distributions
  • Relationships
• Model training
  • Naive vs full models
• Model evaluation
  • In-sample vs out-sample
• Model interpretation
  • Shap, see Explaining "Blackbox" ML Models - Practical Application of SHAP

Templates

• Regression template
• Classification template

Additional resources

• Project template for highly effective data science workflows
• Python library for building highly effective data science workflows
• 4 Reasons Why Your Machine Learning Code is Probably Bad
• Guide to managing data science projects from start to finish