Covers: theory of Linear Regression

- Why is regression useful?
- What's the equation for a linear regression?
- How does linear regression works?

Watch the full video. You can also follow the proposed code if you want to practice (approx. 15 min extra)

Fail to play? Open the link directly: https://www.youtube.com/watch?v=yEUKougrRSk

Siraj Raval

Sandra Lopez-Zamora**Total time needed: **~2 hours

- Learning Objectives
- Understand the concept of Logistic Regression
- Potential Use Cases
- Deep Learning Mathematical Foundations
- Target Audience
- BEGINNERDeep Learning practitioners new to Mathematical foundations

Go through the following **annotated items** *in order*:

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

Previewing stream ** Math and Foundations**

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