Skip to content

🧭 Quick References Guides — Overview

The Quick References section provides streamlined, topic-specific guides for analysts, data scientists, and developers who need fast access to essential methods, workflows, and best practices.
Each guide distills complex topics into actionable insights, allowing for rapid recall and application without needing to search through full-length documentation.
These resources are grouped into key functional areas to support different stages of the analytics and machine learning lifecycle.

  • 🧭 Data Wrangling & EDA — Startup, transformation, and validation guides for preparing datasets and ensuring data integrity.
  • 🧭 Cleaning — Utilities and structured logs for foundational and advanced data cleaning workflows.
  • 🧭 Regression — Linear and logistic regression references, including robust methods and regularization.
  • 🧭 Supervised ML — Algorithm-specific guides for classification models, including decision trees, ensemble methods, and SVMs.
  • 🧭 Clustering Models — Practical quick references for common clustering techniques, from centroid-based to density-based approaches.