Machine Learning, Spring 2019

Course Description

Machine learning allows computational systems to adaptively improve their performance with experience accumulated from the data observed. This course introduces the basics of learning theories, the design and analysis of learning algorithms, and some applications of machine learning.


Course Information


Class Policy

Course Plan (tentative)

datesyllabustodo/donesuggested reading
2/19 topic 1: how can machines learn by embedding numerous features?
linear support vector machine
course slides; LFD e-8.1
2/26 dual support vector machine
kernel support vector machine
course slides; LFD e-8.2
course slides; LFD e-8.3
3/5 soft-margin support vector machine homework 1 announced course slides; LFD e-8.4
3/12 kernel logistic regression
support vector regression
course slides;
extended reading: course slides;
extended reading:
3/19 topic 2: how can machines learn by combining predictive features?
blending and bagging
course slides;
extended reading:
3/26adaptive boosting
decision tree
homework 1 due course slides;
extended reading: course slides;
extended reading:
4/2 no class because of Spring Break homework 2 announced; final project announced
4/9 random forest course slides;
extended reading:
4/16gradient boosted decision tree
topic 7: how can machines learn by distilling hidden features?
neural network
course slides;
extended reading: course slides; LFD e-7.1, e-7.2, e-7.3, e-7.4 (selected parts)
4/23 (shallow explanation of) deep learning course slides; LFD e-7.6
4/30 (shallow explanation of) deep learning
radial basis function network
homework 2 due; homework 3 announced course slides; LFD e-6.3
5/7 no class because instructor is at ICLR
5/14 radial basis function network
matrix factorization
course slides
5/21 modern deep neural network: activation and optimization homework 3 due; homework 4 announced extended reading:
5/28 modern deep neural network: optimization and regularization extended reading:
6/4 convolutional neural network extended reading:
6/11 machine learning for modern artificial intelligence homework 4 due course slides (re-use talk slides at Institute of Information Science, Academia Sinica, Taipei, Taiwan, November 2018)
6/18finale and award ceremony summary slides; final project award presentation slides
6/25 summer vacation started (really?) final project due