Covers: theory of Logistic Regression
Estimated time needed to finish: 15 minutes
##### Questions this item addresses:
• What is the difference between naïve Bayes and Logistic Regression?
• What is logistic regression?
• What advantages has the sigmoid function?
##### How to use this item?

Read the introduction to section 5 and section 5.1

##### Author(s) / creator(s) / reference(s)
Daniel Jurafsky & James H. Martin
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### Logistic Regression

Contributors
Total time needed: ~2 hours
Objectives
Understand the concept of Logistic Regression
Potential Use Cases
Deep Learning Mathematical Foundations
Who is This For ?
BEGINNERDeep Learning practitioners new to Mathematical foundations
Click on each of the following annotated items to see details.
OTHER 1. Sigmoid Function
• How does sigmoid curve look like?
• What's the derivative of the Sigmoid function?
• What's the integral of the Sigmoid function?
10 minutes
VIDEO 2. Regression
• Why is regression useful?
• What's the equation for a linear regression?
• How does linear regression works?
13 minutes
ARTICLE 3. Logistic Regression
• What is logistic regression?
• How can I use logistic regression with an example?
• How can I use logistic regression in Python (Sklearn)?
15 minutes
ARTICLE 4. Logistic Regression
• What is Wrong with Linear Regression for Classification?
• How can logistic regression results be interpreted?
• What are the advantages and disadvantages of Logistic Regression?
15 minutes
BOOK_CHAPTER 5. Logistic Regression
• What is the difference between naïve Bayes and Logistic Regression?
• What is logistic regression?
• What advantages has the sigmoid function?
15 minutes

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