Multiple Linear Regression with Scikit-learn in Python - Supervised Machine Learning
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Learn to implement Multiple Linear Regression using scikit-learn in Python through this 32-minute tutorial that guides you through supervised machine learning concepts. Work with a provided dataset to understand how to handle multiple independent variables, build and train regression models, and evaluate their performance. Access the complete code implementation via GitHub, including the dataset and Jupyter notebook, while exploring practical examples that demonstrate error magnitude calculations and model accuracy assessment. Master the fundamentals of predictive modeling using multiple variables to make accurate predictions in real-world scenarios.
Syllabus
Multiple Linear Regression - Supervised Machine Learning | sklearn - Python
Taught by
Codeynamics