BC2.03b Machine Learning - Dr Doan Nhat Quang

Topic outline

• General
  

  General

  • Announcements Forum
• Guidelines
  

  Guidelines

  Classroom:

  Invitation: Link

  Classroom: Link

  PROJECT

  Presentation + Report Submission: 

  • Project Registration: Link
  • Deadline Report Submission: 23:59 - 07/04/2024
  • Presentation: 16:00 - 19:00 6/4/2024 @801 A21 USTH

  Guidelines for report/presentation:

  • Introduction/Motivation/Contribution: Specify clearly the content of the project;
  • Project process: describe in detail how to build the system/models in the project;
  • Data analysis: study the collected data, and perform statistical analysis on the data;
  • Experiments: show the experimental protocols, calculate the complexity or running time
  • Evaluation and discussion: calculate the quality criteria, compare the obtained results from different models, and propose respectives

  Report: 5-10 pages

  Group: 1-2 member(s)/group

  Presentation: 10' for presentation, 5' for QA (15'/group and all members must be present) 

  
  
• Lecture 1
  

  Lecture 1

  • Lecture 1 - Introduction File
• Lecture 2
  

  Lecture 2

  • Lecture 2 - Feature Selection File
  • Code Sample: L1 Regularization for Feature Selection File
  • Code Sample: Random Forest for Feature Selection File
• Lecture 3
  

  Lecture 3

  • Association Rule Learning File
  • Transaction Database File
• Lecture 4
  

  Lecture 4

  • Lecture 4 - Semi-supervised learning File
• Lecture 5
  

  Lecture 5

  • Reinforcement Learning File
  • Data: MAB File
  • Code: MAB File
  • Code: Q-Learning File