Скачать или смотреть Chapter 3.1 Logistic Regression | Loss Function | Regularization | Machine Learning in Hindi |

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-Sigmoid Function
-Improved Loss function of Logistic regression
-Montonic Functions
-Log transformation
-More Transformation
-Final Logistic Regression Loss Function
-Alternate formulation of loss function
-Intro to Regularization
-Why weights increase in logistic regression loss function
-Big weights = overfitting
-Feature Importance from weight vectors
-L2 - Regularization or Ridge Regression formula
-Hyperparameter Lambda

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Machine Learning using python

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