Print View: COMP7703 - Sem 1 2009 - St Lucia

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

Students will gain a fundamental understanding of a wide range of Machine Learning techniques and algorithms, including supervised and unsupervised learning. Students will also gain an appreciation for the practical applications of machine learning techniques, and will gain experience in implementation and using machine learning methods.

2.2 Learning Objectives

After successfully completing this course you should be able to:

1  Implement and apply machine learning techniques to solve problems
2  Appreciate machine learning research ideas (state-of-the-art) and practice (journal and conference publication, peer review).
3  Understand the main issues and core problems that the field of machine learning is concerned with.
4  Understand the relationships between machine learning and other fields (artificial intelligence, statistics, pattern recognition, optimization).
5  Understand the main theoretical and conceptual issues in machine learning.
6  Understand and be able to apply probabilistic (generative) supervised machine learning models.
7  Understand and be able to apply discriminative supervised machine learning models.
8  Understand and be able to apply techniques for density estimation, dimensionality reduction, clustering and learning sequences.

2.3. Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

GRADUATE ATTRIBUTE	LEARNING OBJECTIVES
*A. IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY*
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.
A3. A comprehensive and in-depth knowledge in the field of study.
A5. An international perspective on the field of study.
A7. An appreciation of the link between theory and practice.
*B. EFFECTIVE COMMUNICATION*
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.	3, 5, 6, 7, 8
B2. The ability to interact effectively with others in order to work towards a common outcome.
B3. The ability to select and use the appropriate level, style and means of communication.
B4. The ability to engage effectively and appropriately with information and communication technologies.	1, 2, 5, 6, 7, 8
B5. The ability to practise as part of an interdisciplinary team.
*C. INDEPENDENCE AND CREATIVITY*
C2. The ability to work and learn independently and effectively.
C3. The ability to generate ideas and adapt innovatively to changing environments.	8
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
C6. The abilities and skills that provide a foundation for future leadership roles.
*D. CRITICAL JUDGEMENT*
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.	2, 5, 6, 8
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.
*E. ETHICAL AND SOCIAL UNDERSTANDING*
E1. An understanding of social and civic responsibility.
E3. An appreciation of the philosophical and social contexts of a discipline.
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.
E7. The ability to work effectively and sensitively across all areas of society.
E8. An understanding of and respect for the roles and expertise of associated disciplines.

5. Assessment

5.1 Assessment Summary

This is a summary of the assessment in the course. For detailed information on each assessment, see 5.5 Assessment Detail below.

Assessment Task	Due Date	Weighting	Learning Objectives
Problem Set/s Assignment 1	8 Apr 09	18%	1, 2, 3, 4
Problem Set/s Assignment 2	20 May 09	18%	1, 2, 3, 4
Exam - during Exam Period (Central) Final Exam	Examination Period	64%	1, 2, 3, 4, 5, 6, 7, 8

5.2 Course Grading

Grade 1, Fail: Fails to demonstrate most or all of the basic requirements of the course: This grade will be awarded when the combined total marks from all assessment is at least 0% but less than 20% of total marks available.

Grade 2, Fail: Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline: This grade will be awarded when the combined total marks from all assessment is at least 20% but less than 45% of total marks available.

Grade 3, Fail: Demonstrates superficial or partial or faulty understanding of the fundamental concepts of the field of study and limited ability to apply these concepts; presents undeveloped or inappropriate or unsupported arguments; communicates information or ideas with lack of clarity and inconsistent adherence to the conventions of the discipline: This grade will be awarded when the combined total marks from all assessment is at least 45% but less than 50% of total marks available.

Grade 4, Pass: Demonstrates adequate understanding and application of the fundamental concepts of the field of study; develops routine arguments or decisions and provides acceptable justification; communicates information and ideas adequately in terms of the conventions of the discipline: This grade will be awarded when the combined total marks from all assessment is at least 50% but less than 65% of total marks available.

Grade 5, Credit: Demonstrates substantial understanding of fundamental concepts of the field of study and ability to apply these concepts in a variety of contexts; develops or adapts convincing arguments and provides coherent justification; communicates information and ideas clearly and fluently in terms of the conventions of the discipline: This grade will be awarded when the combined total marks from all assessment is at least 65% but less than 75% of total marks available.

Grade 6, Distinction: As for 5, with frequent evidence of originality in defining and analysing issues or problems and in creating solutions; uses a level, style and means of communication appropriate to the discipline and the audience: This grade will be awarded when the combined total marks from all assessment is at least 75% but less than 85% of total marks available.

Grade 7, High Distinction: As for 6, with consistent evidence of substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem solving approaches; critically evaluates problems, their solutions and implications: This grade will be awarded when the combined total marks from all assessment is greater than 85% of total marks available.

5.3 Late Submission

Late submissions will incur a penalty of 10% of the total marks received for each day that the submission is late (including weekend days). Submissions more than 5 days late will not be accepted. Late hardcopy submissions should be handed in to the lecturer via the ITEE School Office.

5.5 Assessment Detail

Assignment 1

Type: Problem Set/s
Learning Objectives Assessed: 1, 2, 3, 4
Due Date:
8 Apr 09
Weight: 18%
Task Description: Assignment 1
Criteria & Marking: This assignment will be based on questions from the practical sessions. Students will be awarded marks according to correctness of answers to practical questions. Presentation of answers (e.g code, figures, written responses) is also important when awarding marks.
Submission: Submission box.

Assignment 2

Type: Problem Set/s
Learning Objectives Assessed: 1, 2, 3, 4
Due Date:
20 May 09
Weight: 18%
Task Description: Assignment 2
Criteria & Marking: This assignment will be based on questions completed during the practical sessions. Students will be awarded marks according to correctness of answers to practical questions. Presentation of answers (e.g code, figures, written responses) is also important when awarding marks.
Submission: Submission box.

Final Exam

Type: Exam - during Exam Period (Central)
Learning Objectives Assessed: 1, 2, 3, 4, 5, 6, 7, 8
Due Date:
Examination Period
Weight: 64%
Perusal: 10 minutes
Duration: 120 minutes
Format: Short answer, Problem solving
Task Description: Final Examination
Criteria & Marking: Students will be awarded marks according to correctness of answers to closed-book questions. Part marks will be awarded for working.

6. Policies & Guidelines

This section contains the details of and links to the most relevant policies and course guidelines. For further details on University Policies please visit myAdvisor and the University Handbook of Policies and Procedures.

6.1 Assessment Related Policies and Guidelines

University Policies & Guidelines

An overview of the University’s assessment-related policies can be found on myAdvisor (http://www.uq.edu.au/myadvisor/index.html?page=2910).

Academic Integrity
It is the University's task to encourage ethical scholarship and to inform students and staff about the institutional standards of academic behaviour expected of them in learning, teaching and research. Students have a responsibility to maintain the highest standards of academic integrity in their work. Students must not cheat in examinations or other forms of assessment and must ensure they do not plagiarise.

Plagiarism
The University has adopted the following definition of plagiarism:

Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.

Students are encouraged to read the UQ Academic Integrity and Plagiarism policy (http://www.uq.edu.au/hupp/index.html?page=25128) which makes a comprehensive statement about the University's approach to plagiarism, including the approved use of plagiarism detection software, the consequences of plagiarism and the principles associated with preventing plagiarism.

Feedback on Assessment
Feedback is essential to effective learning and students can expect to receive appropriate and timely feedback on all assessment. For a detailed explanation of the feedback you are entitled to, you should consult the policy on Student Access to Feedback on Assessment. (http://www.uq.edu.au/hupp/index.html?page=25109)

As a student you have a responsibility to incorporate feedback into your learning; make use of the assessment criteria that you are given; be aware of the rules, policies and other documents related to assessment; and provide teachers with feedback on their assessment practices.

There are certain steps you can take if you feel your result does not reflect your performance. Please refer to the myAdvisor web site. (http://www.uq.edu.au/myadvisor/index.html?page=2953)

School of Information Technology and Electrical Engineering Assessment Guidelines

Misconduct

Further to the statement on academic integrity and plagiarism above, students are required to read and understand the ITEE policy on Student Misconduct (http://www.itee.uq.edu.au/about_ITEE/policies/student-misconduct.html).

Late Arrival or Non-attendance at Examinations

The policy and procedure for late arrival or non-attendance at centrally controlled and school-based examinations is set out in the University's Assessment policy (HUPP 3.30.1), section 4.8 at http://www.uq.edu.au/hupp/index.html?page=25109.

In the case that a student requests a special exam for a School-controlled exam, the request will be considered and, if allowed, the timing shall be determined by the course coordinator, in consultation with the School's Chief Examiner where necessary, and in accordance with HUPP 3.30.1. Unless otherwise indicated in the Course Profile, applications must be made in writing to the Head of School no later than 5 days after the exam. Late applications will not be accepted.

Examination Feedback

In addition to the advice above, students wishing to view examination answer scripts and/or question papers should consult with the School office (Room 217, General Purpose South Building [78], St Lucia) regarding arrangements. The ITEE policy on exam script viewing is available at http://study.itee.uq.edu.au/current_students/exam_script_viewing.html.

Supplementary Assessment

If you fail this course you may be eligible for supplementary assessment - see the general award rules and/or your program rules for details. You should note that even though you may be eligible for supplementary assessment under these rules, in some circumstances there may be no practical assessment that can be offered to allow you to meet the minimum passing requirements. These circumstances may include failure based on:

group or team based assessment;
attendance or class participation requirements;
laboratory-based assessment, where laboratories can't practically be made available after classes have finished;
project or thesis-based assessment, where a significant period of time would be required to undertake supplementary assessment;
progressive assessment, where subsequent assessment items build on earlier assessment items; or
multiple assessment items, where it is impractical to offer multiple supplementary assessment items.

If the course coordinator determines that there is no practical supplementary assessment that can be offered to allow you to improve your grade, then you will not be offered supplementary assessment and your grade will remain unchanged.

Calculators in Examinations

Some examinations in the School of Information Technology and Electrical Engineering restrict the type of calculator that can be used. If this course profile does not specify any calculator restrictions, you should check with the course coordinator as to whether any restrictions apply. In some examinations, you may only be permitted to use an EPSA/EAIT approved and lablled non-programmable calculator. It is your responsibility to ensure you have a suitable approved and labelled calculator if required.

6.2 Other Policies and Guidelines

University Policies and Guidelines

Placement Courses
Students on a placement course – also known as a work placement, internship, industry study, industry experience, clinical practice, clinical placement, practical work, practicum, fieldwork, teaching practice – should refer to the University policy, Placement Courses (http://www.uq.edu.au/hupp/index.html?page=25120) for detailed information.

Working with Children
Students whose studies include a professional/work placement, internship, clinical practice, teaching practice or other similar activity which involves them in regular contact with children should refer to the University policy, Working with Children Check - "blue card" (http://www.uq.edu.au/hupp/index.html?page=25004) to find out how to apply for a ‘blue card’.

Students with a Disability
Any student with a disability who may require alternative academic arrangements, including assessment, in the course/program is encouraged to seek advice at the commencement of the semester from a Disability Adviser at Student Support Services. Refer to the University policy, Students with a Disability (Disability Action Plan) (http://www.uq.edu.au/hupp/index.html?page=25122) and to the policy on Special Arrangements for Examinations for Students with a Disability (http://www.uq.edu.au/hupp/index.html?page=25111

Where an adjustment is made to an accredited program, it is the responsibility of the relevant Faculty to liaise with professional and registration bodies regarding the acceptability of the change/s.

Occupational Health and Safety
Undergraduate Students (http://www.uq.edu.au/hupp/index.html?page=25055) and Postgraduate Students (http://www.uq.edu.au/hupp/index.html?page=25057) should be familiar with the University policies on occupational health and safety in the laboratory.

Other School of Information Technology and Electrical Engineering Guidelines

Ethical Clearance

If your course involves assignment or project work involving human subjects or human-related materials, you must investigate the need for ethical clearance and obtain it when required. Information on ethical clearance can be found at http://www.uq.edu.au/research/orps/index.html?page=5064&pid=5256.

Learning Summary

Below is a table showing the relationship between the learning objectives for this course and the broader graduate attributes developed, the learning activities used to develop each objective and the assessment task used to assess each objective.

Learning Objectives

After successfully completing this course you should be able to:

Assessment & Learning Activities

	Learning Objectives
	1	2	3	4	5	6	7	8
Learning Activities
Introduction; Supervised Learning (Lecture)
Bayesian Decision Theory (Lecture)
Supervised Learning (Practical)
Parametric Methods (Lecture)
Bayesian Decision Theory (Practical)
Dimensionality Reduction (Lecture)
Parametric Methods (Practical)
Clustering (Lecture)
Dimensionality Reduction (Practical)
Nonparametric Methods (Lecture)
Clustering (Practical)
Linear Discrimination (Lecture)
Nonparametric Methods (Practical)
Multilayer Perceptrons (Lecture)
Linear Discrimination (Practical)
Local Models (Lecture)
Multilayer Perceptrons (Practical)
Hidden Markov Models (Lecture)
Assessing algorithms, Bagging and Boosting (Practical)
Combining Multiple Learners (Lecture)
Assessing and Comparing (Lecture)
Course Review; Exam Preview (Lecture)
Assessment Tasks
Assignment 1
Assignment 2
Final Exam

Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

	Learning Objectives
	1	2	3	4	5	6	7	8
Graduate Attributes
*A IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY*
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.
A3. A comprehensive and in-depth knowledge in the field of study.
A5. An international perspective on the field of study.
A7. An appreciation of the link between theory and practice.
*B EFFECTIVE COMMUNICATION*
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.
B2. The ability to interact effectively with others in order to work towards a common outcome.
B3. The ability to select and use the appropriate level, style and means of communication.
B4. The ability to engage effectively and appropriately with information and communication technologies.
B5. The ability to practise as part of an interdisciplinary team.
*C INDEPENDENCE AND CREATIVITY*
C2. The ability to work and learn independently and effectively.
C3. The ability to generate ideas and adapt innovatively to changing environments.
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
C6. The abilities and skills that provide a foundation for future leadership roles.
*D CRITICAL JUDGEMENT*
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.
*E ETHICAL AND SOCIAL UNDERSTANDING*
E1. An understanding of social and civic responsibility.
E3. An appreciation of the philosophical and social contexts of a discipline.
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.
E7. The ability to work effectively and sensitively across all areas of society.
E8. An understanding of and respect for the roles and expertise of associated disciplines.

feedback

R. Duda, P. Hart and D. Stork. Pattern Classification, Second edition. Wiley, 2001.

Bishop, C. M. Pattern Recognition and Machine Learning. Springer. 2006

T. Hastie, R. Tibshirani and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. 2001.

D. Hand, H. Mannila and P. Smyth, Principles of Data Mining, MIT Press, 2001.

T. M. Mitchell, Machine Learning, McGraw-Hill, 1997

COMP7703 - Sem 1 2009 - St Lucia - Internal

1. General Course Information

1.1 Course Details

1.2 Course Introduction

1.3 Course Staff

1.4 Timetable

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

2.2 Learning Objectives

2.3. Graduate Attributes

3. Learning Resources

3.1 Required Resources

3.2 Recommended Resources

3.3 University Learning Resources

3.4 School of Information Technology and Electrical Engineering Learning Resources

3.5 Other Learning Resources & Information

4. Teaching & Learning Activities

4.1 Learning Activities

4.2 Other Teaching and Learning Activities Information