Data Science Tutorials

Get started using Git Large File Storage (LFS) in your own repositories to help manage sizeable binary files.

Master the art of visualizing data in Excel using histograms! This step-by-step guide will walk you through various methods, such as built-in charts, formulas, and the Analysis ToolPak, to help you analyze frequency distributions like a pro.

Discover how collaborative filtering powers recommendation systems in e-commerce, streaming, and more. Learn its types, benefits, challenges, and Python implementation.

Master alphabetizing in Excel with built-in tools and formulas. Learn to sort columns, rows, and entire datasets.

Fine-tune the new Gemma model using the finance reasoning dataset to improve its accuracy and adopt the style of the dataset.

Explore the determinant’s role in matrix operations, geometry, and computational methods, with step-by-step calculations in Python and R.

Learn what natural language processing (NLP) is and discover its real-world application, using Google BERT to process text datasets.

Learn feature engineering with this hands-on guide. Explore techniques like encoding, scaling, and handling missing values in Python.

Learn how the NPER() function in Excel calculates the number of periods required to pay off a loan or reach an investment goal. Discover its syntax, use cases, and practical examples.

Learn how forward propagation works in neural networks, from mathematical foundations to practical implementation in Python. Master this essential deep learning concept with code examples and visualizations.

Learn how to use Git rebase to keep your commit history clean and improve collaboration. This guide covers step-by-step instructions, best practices, and common pitfalls to avoid when rebasing branches in Git.

Learn how to copy files to and from S3 using the aws s3 cp command. Explore everything from basic transfers and recursive copying to automation scripts and troubleshooting common errors—all with practical, real-world examples.