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Deep Learning Fundamentals

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    Deep Learning Fundamentals > Unit 3 > Unit 3.2
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    3.2 The Logistic Regression Computation Graph

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    What we covered in this video lecture

    In this lecture, we took the logistic regression model and broke it down into its fundamental operations, visualizing it as a computation graph. If the previous videos were too abstract for you, this computational graph clarifies how logistic regression works under the hood.

    Note that we have only covered the learning algorithm so far. The following videos will show how the training and weight updates work.

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    Quiz: 3.2 The Logistic Regression Computation Graph

    Suppose we have a dataset with two features (Similar to unit 2). The predicted class-membership probability via a logistic regression model is calculated as

    Incorrect. This answer implies that the logistic regression models only uses the first feature.

    Incorrect. This answer implies that the logistic regression models only uses the first feature.

    Correct. In logistic regression for binary classification, we return the class-membership probability for class 1.

    Incorrect. In logistic regression for binary classification, we return the class-membership probability for class 1.

    Please answer all questions to proceed.
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    Unit 3.2

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