Decision making with Genetic Algorithms using DEAP

  • 데이터와 학습
  • 2016-08-14 (일요일) 14:40 - 15:20
  • 영어
  • 102
  • 촬영, 녹화가 가능합니다.

발표 동영상



  • Background
    • Nowadays, many people interested in machine learning because of it’s ‘Super Power'. Among them, one of the  famous method is Deep Neural Network.(a.k.a. Deep Learning) In spite of it’s powerful accuracy and usefulness, It has fatal problem. It is hard to understand for beginners because it needs background knowledge like not only Programming but also Mathematics and Statistics. 
    • Genetic algorithm is natural-inspired machine learning method. Even thought It’s not that trendy tool like deep-learning, It’s easier to understand than other complex machine learning method, also helpful in making decision more efficiently. DEAP is novel framework for Genetic algorithm, and it’s very useful for rapid prototyping and testing of ideas.
  • Goal
    • In this session, We will not focus on difficult matters like face detecting, text generation, but let’s think about problems you may meet in ordinary life. (maybe it could be trivial) Let’s find the best way in 'decision space’  to solve problems using Genetic Algorithms. 
  • Contents
    • Decision Making
    • Genetic Algorithm
      • Basic Theory
      • Practice #1: Basic Genetic Algorithm
    • Multi-Objective Genetic Algorithm 
      • Basic Theory
      • Practice #2: Find the Best Tour Route using NSGA-ii


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