Course Policies

Late Policy

• You can use 2 late day for individual assignment (3 HWs)
• Once you have used all 2 late days, penalty is 25% for each additional late day.
• If you have a verifiable medical condition or other special circumstances that interfere with your coursework please let us know as soon as possible by sending an email to the lecturer and TAs.

Collaboration Policy

We expect you to adhere to the University Honor Code at all times. Failure to adhere to the honor code and our policies may result in serious penalties, up to and including automatic failure in the course.

Credits

Slides and notebooks in this course are based on other open classes or online resources. For example, we gain lots of ideas to prepare BT5153 from the following resources:

• CS224D Deep Learning for Natural Language Processing: a detailed introduction to cutting-edge research in Deep Learning for NLP.
• CPSC 540 Machine Learning: this course focus on probabilistic machine learning, which is provided by Professor Nandi de Freitas
• Machine Learning: ML related course series (in chinese) provided by Professor Hung-yi Lee, National Taiwan University

We have tried our best to cite these resources by giving credits to these original sources. Please contact us if you find materials where the reference is missing or that you would rather have removed.