Practical Machine Learning

Dr. Suyong Eum / Dr. Hua Yang

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Lectures / Tutorials

General information.

	Lecture room: C401
	Friday: 10:30 ~ 12:00

Lecture schedule

The following table provides a brief summary of the tentative topics and a link to a PowerPoint file in pdf format containing the notes. Where errors occur in the notes, updates will be posted as soon as practicable. The notes will be made available prior to lectures where-ever practicable. You will need to use Acrobat Reader to obtain this material as it will be in pdf format.

Week	Topic	Date	Lecturer
W1	Introduction to Machine Learning	APR. 13th	Dr. EUM
W2	Linear models for classification and regression	APR. 20th	Dr. EUM
W3	K-means model and Gaussian Mixture Model (GMM)	APR. 27th	Dr. EUM
W4	Hidden Markov Model (HMM)	MAY 11th	Dr. EUM
W5	Support Vector Machine (SVM) and Kernel trick	MAY 18th	Dr. EUM
W6	Principal Component Analysis (PCA)	MAY 25th	Dr. EUM
W7	Neural Networks	JUN. 1st	Dr. EUM
W8	Convolutional Neural Networks (CNN)	JUN. 8th	Dr. EUM
W9	Tensorflow - CNN implementation	JUN. 15th	Dr. EUM
W10	Recurrent Neural Networkss (RNN) and Long Short Term Memory (LSTM)	JUN. 22nd	Dr. EUM
W11	Tensorflow - RNN / LSTM / GRU implementation	JUN. 29th	Dr. EUM
W12	Generative Models: Variational Auto Encoder (VAE) and Generative Adversarial Network (GAN)	JUL. 6th	Dr. EUM
W13	Tensorflow - VAE / DCGAN implemenation	JUL. 13th	Dr. EUM
W14	Reinforcement Learning (RL):Deep Q Networks (DQN) and Policy Gradient(PG: AC/A3C)	JUL. 20th	Dr. EUM
W15	Tensorflow - DQN / PG / AC implementation	JUL. 27th	Dr. EUM

Tutorial schedule

There will be four tutorial sessions during this semester. The completion of the tutorials will greatly help you to carry out the first assignment. Thus, your participation is highly encouraged. The date and time will be announced in the lecture.

Tutorial sessions will be carried out on the day as shown below from 11:00 to 12:00 at C401.

Week	Topic	Code	Date	Tutor
W2	Introduction to Python	code	APR. 20th	Dr. YANG
W3	Perceptron algorithm with scikit-learn	code	APR. 27th	Dr. YANG
W6	Support Vector Machine (SVM) with scikit-learn	code	MAY. 25th	Dr. YANG
W7	Principal Component Analysis (PCA) with scikit-learn	code	JUN. 1st	Dr. YANG
W10	Tensorflow: Deep Neural Networks(DNN): PART I - Model definition	code	JUN. 20th	Dr. EUM
W11	Tensorflow: Deep Neural Networks(DNN): PART II - Evaluation	code	JUN. 27th	Dr. EUM
W12	Tensorflow: Convolutional Neural Networks(CNN): data loading - Queuerunner	code	JUL. 4th	Dr. EUM

References

1. Christopher M. Bishop “Pattern Recognition and Machine Learning,” Springer, 2011. ISBN-10: 0387310730. (online downloadable)

2. Tom M. Mitchell “Machine Learning,” March, 1997. ISBN: 0070428077. (online downloadable)