Data Science Tutorials

An honest walkthrough of SageMaker Studio Lab—from setting up to running real ML projects—perfect for students, educators, and developers who want a powerful, free development environment.

Learn how the probability mass function defines discrete probability distributions. Explore its properties, examples, and differences from probability density functions.

Learn how to quickly find the middle value of your data using the R median() function. Discover tips for handling missing values and grouping data by categories.

Calculate the average of numeric, logical, and weighted data using R’s built-in mean functions. Understand how to handle missing values and apply the function to vectors and data frames.

Learn what RMSE means in regression analysis, how to calculate it, and when to use it to assess model performance. See Python and R examples with practical interpretations.

Learn about Google’s Project Mariner through real-world examples and a breakdown of its strengths and weaknesses.

Set up a full-stack deep AI research assistant, featuring a React frontend and a LangGraph backend.

Combine cell values smoothly with TEXTJOIN(). Handle delimiters, skip blanks, and simplify your data assembly in Excel.

Step-by-step guide to fine-tuning the Mistral reasoning model on a medical MCQs dataset using the Transformers framework.

Are you having trouble with slow Excel workbooks or large files that are hard to share? This guide shows you simple and advanced ways to reduce Excel file size, improve performance, and make collaboration easier.

Discover quick methods to start a new line in an Excel cell using keyboard shortcuts, formulas, and Find & Replace. Learn platform-specific tips for Windows, Mac, and web-based Excel versions.

Follow these steps to get started running Python scripts in Tableau using TabPy. This will enable you to create modeling and analytical pipelines for your Tableau visualizations.