Regression Models, Multiple Features, 04B

🚀 Course: ML & AI for Civil Engineers 🔁 Module 04: Regression Models 🧠 Lecture B: Multiple Features 👇 Link to the notebook: https://tinyurl.com/28hcl5dv 🚀 Multiple feature linear regression in Python teaches you how to scale features, train with gradient descent, and evaluate models from scratch. This lecture uses NumPy, pandas, and Matplotlib to build scaled feature matrices, prevent data leakage with train-test preprocessing, create vectorized predictions, update weights and bias, track mean squared error, and compare regression models using test error, RMSE, residual plots, and predicted-versus-actual diagnostics. Watch to learn practical machine learning workflow steps for civil engineering, bridge, and housing datasets, then try the code concepts in your own regression projects. ▶️➕🔔 Don't forget to like, subscribe, and hit the notification bell! ⚠️ Disclaimer: AI Voice used. #tutorials, #featurescaling, #numpy, #datapreprocessing, #python, #featurescaling, #numpy, #featurescaling, #standardization, #datavisualization, #python, #gradientdescent, #numpy, #gradientdescent, #numpy, #linearregression, #gradientdescent, #losstracking, #numpy, #linearregression, #modelevaluation, #testmse, #regression, #predictionerror, #datavisualization, #python, #regression, #diagnostics,