Data Science Tutorials

Learn the art of pivoting rows into columns in SQL in Oracle, MySQL, and SQL Server. Explore practical methods with detailed examples to boost your data engineering skills.

Discover how the harmonic mean handles rates and ratios in data science and finance. Learn its calculation methods and when to use it for more accurate analysis.

.loc selects data using row and column names (labels), while .iloc uses numerical indices (positions). Learn how to use both with examples.

Learn how to implement late chunking with Jina AI to improve context preservation and retrieval accuracy in RAG applications.

Understand how to use common table expressions to simplify complex queries for improved readability. Learn the difference between non-recursive and recursive CTEs.

Learn what prompt caching is and how to use it with Ollama to optimize LLM interactions, reduce costs, and improve performance in AI apps.

Learn to manage dotfiles for a consistent configuration across systems and for an improved workflow. Ensure compatibility with Unix-based systems.

Discover how to leverage the power of ChatGPT for Excel to boost your productivity and unlock the full potential of Excel.

Learn the first principles of Proximal Policy Optimization, including its implementation in PyTorch with Gymnasium!

Learn how to detect multicollinearity in regression models using the variance inflation factor (VIF), a key diagnostic tool. This tutorial explains how VIF is calculated, how to interpret its values, and techniques for addressing high VIF to improve the reliability of your regression modeling.

Learn how third normal form (3NF) can help you organize your databases more efficiently by removing redundancy and minimizing dependency issues. See how decomposing tables can simplify data management.

From ancient Egyptian builders to modern data science, discover how a^² + b^² = c^² revolutionized mathematics and continues to shape our technological world.