Machine Learning from Scratch: Concepts, Examples and Tools
- LecturerDr. Da-Cheng Juan (Google)
Host: Wen-Lian Hsu - Time2016-01-06 (Wed.) 10:30 ~ 12:30
- LocationAuditorium 106 at IIS new Building
Abstract
“Machine learning is a buzzword, but what does it mean?” “What are the most important machine-learning concepts?” “Is there any crash course for machine learning?”These three questions serve as the motivation to attend this talk. In this talk, we will provide a complete end-to-end workflow for conducting machine learning. This workflow includes (a) data representation, (b) machine-learning concepts, and (c) standard procedure to train, test, and evaluate a learned model. Concrete examples, tools and several advanced topics are also provided along the talk.
BIO
Da-Cheng received his Ph.D. from the Department of Electrical and Computer Engineering and his Master’s from Machine Learning Department, both at Carnegie Mellon University. His research interests include applied machine learning and energy-efficient computing. Da-Cheng has published more than 15 papers in these fields. In addition to research, he also enjoys algorithmic programming and has won several awards from major programming contests. Currently, Da-Cheng is with Google Inc., developing machine-learned recommendation system.