Lecture 6 – Logistical regression and classification#

Logistical classification is a basis knowledge to understand the logistical regression and the following articial neural network, such as the activation functions, and the tranfer functions.

Contents of this lecture

*Simple Logistic classification *Multiclass classification *Logistic regression

  • Decision boundary

  • Regression: parameter estimation

NB: This lecture is largely referred from Prof. Ng’s course!

  • file: contents/P3_machine-learning/l06_logistic.md title: Lecture 6 – Logistical regression and classification sections:

    • file: contents/P3_machine-learning/tutorials/lecture6/examples.ipynb title: Computer Examples

    • file: contents/P3_machine-learning/tutorials/lecture6/exercise.ipynb title: Computer Excercises

  • file: contents/P3_machine-learning/l07_trees.md title: Lecture 7 – Decision trees and ensemble algorithm sections:

    • file: contents/P3_machine-learning/tutorials/lecture7/examples.ipynb title: Computer Examples

    • file: contents/P3_machine-learning/tutorials/lecture7/exercise.ipynb title: Computer Excercises

  • file: contents/P3_machine-learning/l08_boost.md title: Lecture 8 – Boosting methods (XGBoost) sections:

    • file: contents/P3_machine-learning/tutorials/lecture8/examples.ipynb title: Computer Examples

    • file: contents/P3_machine-learning/tutorials/lecture8/exercise.ipynb title: Computer Excercises

  • file: contents/P3_machine-learning/l09_svm.md title: Lecture 9 – Support vector machine

  • file: contents/P3_machine-learning/l10_ann.md title: Lecture 10 – Artificial neural network