AI-Assisted Sensor Predictive Models Using Polynomial Regression скачать в хорошем качестве

AI-Assisted Sensor Predictive Models Using Polynomial Regression

AI-Assisted Predictive Models Using Polynomial Regression A step-by-step engineering workflow from fundamentals to AI-assisted validation This video presents a complete workflow for building predictive models using polynomial regression, developed as part of an Engineering Computation course project. ================================ References and Source Code ================================ Article: https://ccitonline.com/wp/2025/12/11/ai-as... Presentation Material: https://github.com/epsi-rns/kom-tek/tree/m... Background: https://epsi.bitbucket.io/statistics/2020/... Source Code: https://github.com/epsi-rns/codecase/tree/... -================================ 𝐌𝐀𝐈𝐍 𝐏𝐑𝐄𝐒𝐄𝐍𝐓𝐀𝐓𝐈𝐎𝐍 ================================ Overview of the complete engineering workflow: from numerical foundations to AI-assisted validation. -------------------------------- 𝐒𝐓𝐀𝐆𝐄 𝐈 – 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 𝐌𝐨𝐝𝐞𝐥 -------------------------------- • Polynomial interpolation and curve fitting • Linear, quadratic, and higher-order models • Accuracy comparison and visual validation -------------------------------- 𝐒𝐓𝐀𝐆𝐄 𝐈𝐈 – 𝐂𝐨𝐝𝐢𝐧𝐠 𝐑𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭 -------------------------------- • Spreadsheet (Excel) to Python transition • Matrix-based analytic methods • Script refactoring and validation • Visualization using Matplotlib -------------------------------- 𝐒𝐓𝐀𝐆𝐄 𝐈𝐈𝐈 – 𝐀𝐈 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭 -------------------------------- • AI as a supporting tool, not a replacement • Rule-based validation and controlled workflows • Localhost vs shared server testing • Reproducibility and stability considerations