January 24th: Homework 1 is released
here. The analytical problems are due
February 12th, 5pm; the programming assignment is due February 19th, 5pm.
You will receive 0 points for analytical homeworks handed in after 5pm, February 16th, or
for programming assignments handed in after 5pm, February 23rd.
Please ignore the due dates on the homework pdf. We have extended the due
dates, due to the cancelled class on January 27th.
Files for the programming assignment:
count_freqs.py,
eval_ne_tagger.py,
ner_train.dat,
ner_dev.dat,
ner_dev.key.
Submission Instructions
- Analytical part: problems must be submitted in hard copy (either hand-written or printed) to the box in front of 723 CEPSR/Shapiro.
- Programming assignments: Place the files for all problems in a directory named [your_uni]_h[X] , where X is the number of the programming assignment. For instance if your uni is xy1234 and you are submitting the first programming assignment, the directory should be called xy1234_h1. Either zip or tar and gzip the directory and upload it to the directory for programming assignment X on the Courseworks page for this class.
- Update on late policy: we will give students 5 "free" days that can be used as they wish across the 4 problem sets. Specifically, we will not penalize the first 5 late days that a student incurs on problem sets. After that, the penalties posted on the problem sets will apply (e.g., 5 points per day late on the first problem set). The final (0 point) deadline will still apply.
Programing Assignments Policy and Guidelines
- Your code should compile and run on the CLIC machines. We recommend solving problems in Python (<= v. 2.7 / 3.0), Java (<= v.1.6), or Perl (<= v 5.10) to ensure compatibility. If you want to use any other language, please request approval from the TAs before you start coding.
- Document your code! Undocumented code will result in lower scores.
- Write a brief report describing results of experiments, any observations you made, design choices and instructions on how to build (if necessary) and run your implementation (command line arguments, whether data is fed to your program on stdin or from a file, etc.). The report is part of your solution and will be scored. It can be in plain text or PDF.
- Make sure your program implements any specific functionality we ask for (input/output format etc.).
- Efficiency of your implementation matters only when we ask for it (your algorithms should have desired performance and space requirements).
- You should be able to solve all problems using pre-installed standard libraries. Do not use any NLP or machine learning libraries. If you choose to use third-party libraries or modules (e.g numeric computing frameworks such as numpy), make sure they are installed on CLIC. When in doubt if it is okay to use third-party code ask the TAs.
- Please separate your report into sections. For example, for each
problem describe
Part1: how to run your code step by step (make sure your code can run on CLIC).
Part2: performance for your algorithm (including precision, recall,
and F-score).
Part3: observations and comments about your experimental results.
Part4: any additional information that is requested in the problem.
Group Work and Academic Honesty Policy
All problems must be solved individually. You may discuss the problems with other students, but you have to do the write-up and implementation yourself. We will check homework assignments for duplicates. Violations will result in a grade of zero and further steps may be taken in accordance with the CS department's academic honesty policy.
