Day 1
Day 2
- Introduction to NLP, IR, and machine learning (pdf)
- Reuters news dataset for the practical session (zip). It is highly recommended that you pre-download this data before the afternoon session to avoid network congestion in the classroom.
- Example code for the practical session. You may have different code, of course, and different ideas.
- Output from this code.
Day 3
Project Checkpoint on Day 3
- If you haven’t chosen a project topic, do so ASAP.
- If you haven’t spoken to your project mentor, do so today.
- If you don’t know what method your project will be using, figure out by end of today by talking to lectures and TAs. This will often require reading 1 or 2 papers, get started ASAP if you haven’t.
- If you don’t know what data you will be using, figure out by Thursday morning.
Day 4
- Slides for lecture on Dynamic Networks (Note that this contains links to film clips which are not contained in the PDF, but which will be shown in the class.)
- For the practical session:
- We will be investigating a model from Stattner et al (2011), “Diffusion in Dynamic Social Networks: Application in Epidemiology”, Lecture Notes in Computer Science v 6861, pp. 559-573;
- From the lecture, here is a simulation of an SIR model using networkx in Python;
From the lecture, here visualises the networks created from the Python script above.
Participant Yi Zong created a very nice solution for the practical session and with his agreement I am placing his contribution here, as an example of how to meet the stated goals. You may find his additions to the sir.py code here.
Day 5
- 9am - 1:30pm Work on your projects and prepare presentations (lunch provided)
- Presentation:
- Every team is allocated 5 minutes plus 2 minutes for questions and presentation switching.
- Your 5 minutes can be allocated as: problem statement and how you did it (2.5 min), your results so far, and what was the most interesting/revealing/surprising/difficult (1.5 min), outlook: what more can you do if … you had another week, more data, etc (1 min)
- It is up to you how many people in your team will present, and who presents what.
- 1:30pm - 2pm break
- 2:00pm - 3:30pm Project presentations
3:30pm - 4pm
- Students: fill out an anonymous online course feedback here
- Lectures: tally the project votes, decide on prizes
- 4pm - 4:30pm
- Prizes, group photo, wrap up