Machine Learning Seunghun Lee Kang Hee Lee Professor

수업 참고 자료 • Introduction to Machine Learning with Python • 파이썬 데이터 사이언스

Categories of Machine Learning • Supervised Learning - Classification(분류), Regression(회귀) ex) Naïve Bayes, k-Nearest

목차 • Supervised Learning 1. classification – Decision Tree • Unsupervised Learning 1. clustering

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

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