[Course 1] Neural Networks and Deep Learning. W3 - Shallow Neural Networks

[Coursera] Neural Networks and Deep Learning 3주차 강의 (Shallow Neural Networks)를 수강하며 작성한 필기 노트입니다. 

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1. Neural Networks Overview

 

2. Neural Network Representation

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3. Computing a Neural Network's Output

 

4. Vectorizing Across Multiple Examples

 

5. Explanation for Vectorized Implementation

 

6. Activation Functions (1)

 

6. Activation Functions (2)

 

7. Why do you need Non-Linear Activation Functions?

 

8. Derivatives of Activation Functions

 

9. Gradient Descent for Neural Networks (1)

9. Gradient Descent for Neural Networks (2)

 

10. Backpropagation Intuition (Optional) (1)

10. Backpropagation Intuition (Optional) (2)

 

11. Random Initialization (1)

 

11. Random Initialization (2)

 

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