Deep Learning - Deep Neural Network for Beginners Using Python - Output Function Implementation

The video tutorial explains the transition from using WX plus B as an output function to incorporating the sigmoid function for logistic regression. It details the definition of an output formula that takes features, weights, and bias as inputs. The implementation of the sigmoid function using the dot product and bias is demonstrated. The tutorial concludes with an overview of logistic regression and mentions upcoming topics.

What is the new output function being used instead of WX plus B?

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What parameters does the output function receive?

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What is the purpose of adding a bias in the output function?

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How is the dot product of X and weights calculated in the implementation?

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What is the next topic that will be covered after the output function?

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