Скачать или смотреть Gauss-Seidel Method Tutorial: Faster Than Jacobi?

Discover the Gauss‑Seidel method and see how it solves systems of linear equations faster than the classic Jacobi iteration. In this step‑by‑step tutorial we break down the theory, the convergence criteria, and the stopping condition, then walk through a complete Python implementation that you can run in Google Colab or on your own machine.

What you’ll learn:
✅ The intuition behind the Gauss‑Seidel iterative algorithm – how it updates each variable as soon as a new value is available
✅ How to set an initial guess and choose a tolerance that balances speed and accuracy
✅ A full Python script that solves a 3‑variable example, with detailed comments and performance tips
✅ Practical applications in engineering, data analysis, and scientific computing, including why the method shines for large, sparse systems

👉 Grab the full source code (including a Jupyter notebook) from our GitHub repo: https://github.com/jubranakram/solvin...

This video is part of our Systems of Linear Equations series, covering LU‑Decomposition, QR factorization, Cholesky, and more. Perfect for students, engineers, and researchers who want to master numerical methods with clear, executable examples.

💡 If this tutorial helped you, hit the like button, share it with your classmates, and subscribe for the complete playlist. Drop a comment below with your questions, your own code tweaks, or requests for the next method you’d like to see. Let’s discuss how you can integrate Gauss‑Seidel into your own projects!

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