The assessment of this unit consists of three assignments and a final exam. You will submit the solutions to the three assignments via iLearn by the due date. The final examination is a closed book examination, and will be taken in person during the exam period.

Late Assessment Submission Penalty

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted.  For example, if the assignment is worth 8 marks (of the entire unit) and your submission is late by 19 hours (or 23 hours 59 minutes 59 seconds), 0.4 marks (5% of 8 marks) will be deducted. If your submission is late by 24 hours (or 47 hours 59 minutes 59 seconds), 0.8 marks (10% of 8 marks) will be deducted, and so on. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration.

Assessments where Late Submissions will be accepted

• Assignment 1 - YES, Standard Late Penalty applies
• Assignment 2 - YES, Standard Late Penalty applies
• Assignment 3 - YES, Standard Late Penalty applies
• Exam - NO, unless Special Consideration is Granted

Supplementary Exam

If you receive Special Consideration for the final exam, a supplementary exam will be scheduled after the normal exam period, following the release of marks. By making a special consideration application for the final exam you are declaring yourself available for a resit during the supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments. Please ensure you are familiar with the policy prior to submitting an application. Approved applicants will receive an individual notification one week prior to the exam with the exact date and time of their supplementary examination.

Requirements to Pass this Unit

To pass this unit, you must achieve a total mark equal or greater than 50%. This unit does not have hurdle assessments.

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.  

During most of the weeks, there will be 2 hours of lectures and 2 hours ot Practicals. All the required software will be installed in the computers of the PC labs allocated for the Practicals but you are free to bring your own device and install the software.

Lectures and practicals start on Week 1.

Delivery Modes

All lectures and Practicals are delivered in campus. The lectures will also be recorded and recordings of the lecture will be available via iLearn. There will not be recordings of the Practical sessions.

Methods of Communication

We will communicate with you via your university email or through announcements in iLearn. Queries to convenors can be made via the Contact tool in iLearn or sent to diego.molla-aliod@mq.edu.au from your university email address.

Reading

Every week there will be a list of required and recommended readings. The list will be maintained in iLearn.

Most of the contents of the unit will be based on the following books:

• Steven Bird, Ewan Klein, Edward Loper. Natural Language Processing -- Analyzing Text with Python and the Natural Language Toolkit. Available online. 
• François Chollet (2021). Deep Learning with Python, 2nd Edition. Manning Publications. Available in the library.

• Dan Jurafsky and James H. Martin (2023), Speech and Language Processing (3rd ed. draft). Available online. 

• Valliappa Lakshmanan, Martin Görner, Ryan Gillard (2021), Practical Machine Learning for Computer Vision. O'Reilly. Available in the library.

• Mohammed Elgendy (2020), Deep Learning for Vision Systems. O'Reilly. Available in the library.

Software

The main software for this unit is Anaconda for Python 3.11 with the following packages:

1. numpy
2. scipy
3. pandas
4. nltk
5. scikit-learn
6. scikit-image
7. gensim
8. tensorflow
9. opencv
10. pillow

Unit Web Page

Note that the majority of the unit materials is publicly available while some material requires you to log in to iLearn to access it.

The unit will make extensive use of discussion boards hosted within iLearn. Please post questions there, they will be monitored by the staff on the unit.

Week 1 classes

Lectures and practical classes will start on week 1.

The following schedule is tentative and is only an indication of the actual contents. The final schedule will be available in iLearn.

The assessment weight has changed. This offering, assessment weight of the exam has been reduced from 50% to 30% of the unit assessment, and the assessment weights of the assignments have been increased.