Lec-6.20 Logistic Regression Part-I (Arif Butt @ Data Science)
01:53 Learning Agenda
03:29 Logistic Regression (What, Why and How)
06:27 Types of Logistic Regression
08:14 Linearly Separable Data
11:46 Assumptions for Logistic Regression
13:38 Linear vs Logistic Regression
19:15 Logistic Regression using Single Layer Perceptron (Step Function)
28:20 Algorithm to Calculate the weights for i/p features
37:14 Coding Example: Using NumPy and Perceptron Logic (Step Function)
44:07 Coding Example: Using Scikit-Learn Logistic Regression Model
47:20 Limitation of using Step Function
50:07 Using Sigmoid Function
55:00 Coding Example: Using NumPy and Perceptron Logic (Sigmoid Function)
email: [email protected], [email protected], [email protected]
Lecture Slides and Resources: http://arifbutt.me
Jupyter notebooks: https://github.com/arifpucit/data-sci...