Covers: theory of Logistic Regression
Estimated time needed to finish: 15 minutes
Questions this item addresses:
  • What is Wrong with Linear Regression for Classification?
  • How can logistic regression results be interpreted?
  • What are the advantages and disadvantages of Logistic Regression?
How to use this item?

Read section 4.2 of the book and follow the proposed example

Author(s) / creator(s) / reference(s)
Christoph Molnar
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Recipe
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Logistic Regression

Collaborators
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

Concepts Covered

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