Data Science Tutorials

Use the tabulate library in Python to create well-formatted tables. Learn about its advanced features and options for customizing table appearance.

Simplify your data models with Excel’s Goal Seek, one of its powerful What-If Analysis tools. Solve real-world problems like loan payments and revenue targets.

Learn how Chebyshev distance offers a unique approach to spatial problems. Uncover its applications in robotics, GIS, and game development with coding examples in Python and R.

Create compelling pie charts in Tableau with clear step-by-step instructions for importing data, adjusting sizes, and customizing colors. Discover advanced methods like grouping categories and adding filters.

Learn how to create customizable pivot tables in Power BI with advanced conditional formatting and some optimization tips.

Learn how to fine-tune Meta AI's SAM 2 using the Chest CT Segmentation dataset to improve the model's image segmentation performance in medical image analysis.

Learn how to fine-tune LLMs on custom datasets, evaluate performance, and seamlessly export and serve models using the LLaMA-Factory's low/no-code framework.

Learn how to create, edit, delete, and implement hierarchies in Power BI.

Learn how to fine-tune TimeGPT, the first foundational model for time series datasets, for forecasting and anomaly detection with just a few lines of code.

Learn how to install Cursor AI on Windows, macOS, and Linux, and discover how to use it through 10 different use cases.

This article teaches you about numerical optimization, highlighting different techniques. It discusses Python packages such as SciPy, CVXPY, and Pyomo and provides a practical DataLab notebook to run code examples.

A database schema provides a comprehensive blueprint for the organization of data, detailing how tables, fields, and relationships are structured. Read to learn about the schema types, such as star, snowflake, and relational schemas.