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Residual sum of squares with Python | Root Mean Squared Error with Python - P5 RSS - Residual sum of squares Github link for python and .csv file - https://github.com/technologycult/PythonForMachineLearning/tree/master/Part30-31-32-33-34-35 MSE - Mean Squared Error RMSE - Root Mean Squared Error In statistics, linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the response given the values of the predictors, rather than on the joint probability distribution of all of these variables, which is the domain of multivariate analysis. Linear regression was the first type of regression analysis to be studied rigorously, and to be used extensively in practical applications. This is because models which depend linearly on their unknown parameters are easier to fit than models which are non-linearly related to their parameters and because the statistical properties of the resulting estimators are easier to determine. RSS = ((y_test - y_predtest)**2).sum() MSE = np.mean((y_test - y_predtest)**2) RMSE = np.sqrt(MSE) All Playlist of this youtube channel ==================================== 1. Data Preprocessing in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPuOjFcbnXLFvSQaHFK3ymUW 2. Confusion Matrix in Machine Learning, ML, AI https://www.youtube.com/playlist?list=PLE-8p-CwnFPvXzvsEcgb0IZtNsw_0vUzr 3. Anaconda, Python Installation, Spyder, Jupyter Notebook, PyCharm, Graphviz https://www.youtube.com/playlist?list=PLE-8p-CwnFPsBCsWwz_BvbZZHIVQ6wSZK 4. Cross Validation, Sampling, train test split in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPsHtol5WXHhq_B3kQPggHH2 5. Drop and Delete Operations in Python Pandas https://www.youtube.com/playlist?list=PLE-8p-CwnFPtvqVVK7QVFsMvDvp2YgCnR 6. Matrices and Vectors with python https://www.youtube.com/playlist?list=PLE-8p-CwnFPsndwnZnL7nXW5mIrdRmgdg 7. Detect Outliers in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPvyCX35yES5D9W7vThiUzwk 8. TimeSeries preprocessing in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPv10bru3719xzDNIgbO6hXA 9. Handling Missing Values in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPvOec0LZ40Bt8OQcbLFa236 10. Dummy Encoding Encoding in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPvu7YriqMZsL9UDbqUUk90x 11. Data Visualisation with Python, Seaborn, Matplotlib https://www.youtube.com/playlist?list=PLE-8p-CwnFPuYBYsmbfMjROOCzKjCwyMH 12. Feature Scaling in Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPtwpVV3FwzwYZYR5hT3i52G 13. Python 3 basics for Beginner https://www.youtube.com/playlist?list=PLE-8p-CwnFPu-jseUMtc4i47jQZN4PNbf 14. Statistics with Python https://www.youtube.com/playlist?list=PLE-8p-CwnFPta0COlxS6E5u14m5ouzbRU 15. Sklearn Scikit Learn Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPtAGb29r8F7up9ilZUXt3l1 16. Python Pandas Dataframe Operations https://www.youtube.com/playlist?list=PLE-8p-CwnFPv_63lkT_Tztiwknv_zGTNy 17. Linear Regression, Supervised Machine Learning https://www.youtube.com/playlist?list=PLE-8p-CwnFPslDi6sfFbFK4KXcVlLwaOM 18 Interiew Questions https://www.youtube.com/playlist?list=PLE-8p-CwnFPt7VBhcnh82y0autSzuOrZp 19. Jupyter Notebook Operations https://www.youtube.com/playlist?list=PLE-8p-CwnFPtqkFd67OZcoSv4BAI7ez5_ Key Highlights & Overview: Learning <strong>Root Mean Squared Logarithmic Error Python</strong> requires clear step-by-step guidance and practical hands-on visual demonstrations. Explore curated video courses, expert walkthroughs, and detailed lesson notes today on <strong>TutorTube</strong>.