南理工机器学习课件.pdf

Lecture Slides for Machine Learning XUELEI HU School of Computer Science Engineering Nanjing University of Science Technology xlhu@ Course Information Home page: /ml.html Reference books: Pattern Recognition and Machine Learning; Chris Bishop The Elements of Statistical Learning: Data Mining, Inference, and Prediction; Trevor Hastie, Robert Tibshirani, Jerome Friedman Tom M. Mitchell, Machine Learning, McGraw Hill, 1997. Ethem Alpaydin, Introduction to Machine Learning MIT Press, 2004. Lecturer: Xuelei Hu (xlhu@, Rm. 720) Grading: Assignments (40%), Final Project (60%) Start early and do not plagiarize! 2 Enjoy☺ ML is becoming ubiquitous in science, engineering and beyond This class should give you the basic foundation for applying ML and developing new methods The fun begins… 3 CHAPTER 1: Introduction What is Machine Learning ? Study of algorithms that improve their performance at some task with experience Data Understanding 5 What is Machine Learning? A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E. Tom M. Mitchell Machine learning is programming computers to optimize a performance criterion using example data or past experience. Ethem Alpaydin 6 Why is Machine Learning Important? Human expertise does not exist