The video discusses the intuition for logistic regression classification.
Timeline
(Python 3.8)
00:00 - Outline of video
00:25 - Classification
02:47 - Classification type: Binary
03:36 - Classification type: Multiclass
04:38 - Linear fit
07:13 - * * * CORRECTION * * *: slide title should say "Sigmoid fit" instead of "Linear fit"
08:40 - Logistic Sigmoid Function
10:14 - Sigmoid function example
11:56 - Softmax function (or Normalized Exponential)
12:43 - Softmax function example
14:24 - Cost function
18:10 - What is odds, log(odds), logit?
20:05 - Interpret Logistic Regression results? Statsmodels: Logit Regression Results
20:05 - Interpret Logistic Regression results? Statsmodels: Logit Marginal probability
27:24 - Code snippet
28:30 - Ending notes
