Channel: Learn By Watch

Category: Education

Tags: logistic regression vs linear regressionoptimization algorithmslogistic regression learning algorithmsigmoid functionneural networkslogistic regression examplelogistic regression explainedlinear regression machine learningwhat is logistic regressionlogistic regression machine learningmachine learning tutorialmachine learning for beginnerslogistic regressionmachine learning full coursegradient descentlogistic regression cost function

Description: Logistic regression is a statistical model that in its basic form uses a logistic function to model a binary dependent variable, although many more complex extensions exist. In this video you will learn about these topics: ● Failure of linear regression - Saw two the cases where linear regression fails. Firstly, in classification problems and secondly when we have a non linear decision boundary ● Sigmoid function - Formula of sigmoid function and how it is useful in classification problems ● Hypothesis function - Hypothesis function for logistic regression ● Cost function for logistic regression ● Vectorised implementation - This method is faster than applying normal for loop ● Gradient descent - Gave the algorithm of gradient descent and explained how it can help in reducing the cost function and make the model better. ● Vectorised gradient descent - A better implementation of gradient descent which takes much less time