Machine Learning Seunghun Lee Kang Hee Lee Professor Slides: 11 Download presentation Machine Learning Seunghun Lee, Kang. Hee Lee Professor : Hyun-chul Kim 2020. 05. 20 Network Data Science Lab 1 수업 참고 자료 • Introduction to Machine Learning with Python • 파이썬 데이터 사이언스 핸드북 Network Data Science Lab 2 Categories of Machine Learning • Supervised Learning - Classification(분류), Regression(회귀) ex) Naïve Bayes, k-Nearest Neighbor, Decision Tree, Random Forest, Logistic Regression, Neural Network, etc. • Unsupervised Learning - Clustering(군집화), Dimensionality reduction(차원 축소) ex) k-means, PCA, SVD • Semi-supervised Learning - supervised + unsupervised • Reinforcement Learning Network Data Science Lab 3 목차 • Supervised Learning 1. classification – Decision Tree • Unsupervised Learning 1. clustering – K-means Network Data Science Lab 4 Supervised Learning Classification – Decision Tree Network Data Science Lab 5 Decision Tree(의사 결정 트리) Network Data Science Lab 7 Train : Test : Validation Network Data Science Lab 10 Thank you! Q&A Seunghun Lee – mr. leesh 90@gmail. com Kanghee Lee – lkh 7054@gmail. com Laboratory : 본관 C-404 c Network Data Science Lab 11 So-hee kang utscAaouHee joo leePromotion from assistant to associate professorConcept learning task in machine learningAnalytical learning in machine learningPac learning model in machine learningPac learning model in machine learningInductive and analytical learning in machine learningInductive analytical approach to learningInstance based learning in machine learningInductive learning machine learning