The computing resource is endorsed by Paperspace and Google Cloud
Lecturers
(Note: please use Google group to ask questions)- Liangliang Cao (liangliang.cao_at_gmai)
- Xiaodong Cui (xdcuibruin_at_gmail.com)
- Kapil Thadani (kapil_at_cs.columbia.edu)
- Guest lecturer: Markus Nussbaum-Thom (nussbaum_at_us.ibm.com)
- Guest lecturer: Nikolai Yakovenko (nickyakovenko_at_gmail.com)
- Guest lecturer: Shiyu Chang (mnbvcxz210_at_gmail.com)
Teaching Assistants
(Note: please use Google group to raise questions)- Chad DeChant (chad.dechant_at_columbia.edu)
- Yizhou Wang (yw2875_at_columbia.edu)
Office hour
Every Wednesday at 6:15 on the 6th floor of MuddOr contact Chad (chad.dechant_at_columbia.edu) to schedule.
Course Introduction
This graduate level research class focuses on deep learning techniques for vision, speech and natural language processing problems. It gives an overview of the various deep learning models and techniques, and surveys recent advances in the related fields.
This course uses Keras and theano as the primary programminging tool. However, other toolkits including Tensorflow, Torch, Caffe, MxNet, PaddlePaddle are also welcome. GPU programming experiences are preferred although not required.
Frequent paper presentations and a heavy programming workload are expected.
Grading
- 60% project
- 30% homework and paper presentation
- 10% participation