Details of the workshop

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

	Contents of the workshops	Time / Date	Lecturer
1st Workshop	Introduction to Machine Learning (download) - Overview of Machine Learning Topics + tools - Google Cloud setup for the workshops - Discussion on the direction of the workshops during the semester	10am - 11:30am, OCT. 12th (Fri.)	Dr. EUM
2nd Workshop	Support Vector Machine (SVM) with Principal Component Analysis (PCA) (download) - Lecture on SVM and PCA - Hand-on experience: data dimension reduction and classification (MNIST data)	10am - 12:00pm, OCT. 23th (Tues.)	Dr. EUM / Dr. HUA
3rd Workshop	Convolutional Neural Networks (CNN) and Style Transfer (download) - Lecture on Neural Nets and CNNs - Hand-on experience: Style-transfer (theory + implemenation)	10am - 12:00pm, NOV. 6th (Tues.)	Dr. EUM
4th Workshop	Recurrent Neural Networks (RNN) (download) - Lecture on RNN + LSTM + Seq-to-Seq and Attention mechanism - Hand-on experience: Tacotron - speech synthesis (tentative ...)	10am - 12:00pm, NOV. 20th (Tues.)	Dr. EUM
5th Workshop	Reinforcement Learning (RL) (download) - Lecture on RL + DQN + PG - Hand-on experience: CartPole game using OpenAL Gym	10am - 12:00pm, DEC. 4th (Tues.)	Dr. EUM
Location: C401 (Graduate School of Information Science and Technology)

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)