• Homework is generally provided as iPython Notebook Worksheets (.ipynb).
• You will be asked to download these worksheets and complete them, then submit your results by mail in PDF format to hw-2012ws-nlpa@iupr.com.
• The recommended way to generate a PDF from a worksheet is: Open worksheet in browser -> print view -> save file as "PDF"
  
• The mail's subject line should be HWX with X being the serial number of the homework.
• The homework should be done in teams of two. You can choose your own partner. If you don't find somebody, we will help you in the first tutorial
• Make sure the PDF contains your names and e-mail addresses at the top.
• The homework has to be handed in before a given point of time, generally eight days after the task has been published.
• If you need or want to resubmit just reply to your original email and change the to field to hw-2012ws-nlpa@iupr.com. 

General comments regarding the homework:

• The homework / task are very important to understand the contents of the lecture.
• The tasks can be solved with the contents of the lectures. They require only libraries, functions and tools covered in the lecture (plus the standard libraries sys, os, glob, und re). If you think, you need other libraries, contact the tutors.
• Use the hints and code fragments in the provided worksheets.
• The tasks should only take a few hours. If they take much longer, contact the tutors.

Homework 1:

• HW2 - Improve Tagging with Wordnet.ipynb
• Deadline for this part is the 15th of January at 23:59.
• Example Solutions: ipynb pdf  NEW
• HW2 - Classifier-Based Tagging.ipynb 
• Deadline for this part is the 15th of January at 23:59.
• Links:
• NLTK Tag Package (Source @ github)
• Machine Learning 101
• Text feature extraction
• Example Solutions: ipynb pdf NEW