Machine Learning - COMPX310 (2020)
This paper introduces Machine Learning (ML) which is the science of making predictions. ML algorithms strive to be fast and highly accurate, while processing large datasets. This paper will use standard Python-based ML toolkits to teach the fundamentals of ML.
Paper Information
| Points: | 15.0 |
|---|---|
| Prerequisite(s): | COMP103 or COMPX101 or ENGG182 or ENGEN103 and STAT121 or STATS121 or STATS111 or ENGEN102. |
| Internal assessment / examination: | 100:0 |
| Restriction(s): | COMP316 |
Trimesters and Locations
| Occurrence Code | When taught | Where taught |
|---|---|---|
| 20A (HAM) | A Trimester : 2 Mar 2020 - 28 Jun 2020 | Hamilton |
| 20A (TGA) | A Trimester : 2 Mar 2020 - 28 Jun 2020 | Tauranga |
Timetabled Lectures for Machine Learning (COMPX310)
| Day | Start | End | Room | Dates |
|---|---|---|---|---|
| COMPX310-20A (HAM) | ||||
| Mon | 11:00 AM | 12:00 PM | L.G.03 | Mar 2 - May 17 |
| Thu | 3:00 PM | 4:00 PM | S.G.01 | Mar 2 - May 17 |
| COMPX310-20A (TGA) | ||||
| Mon | 11:00 AM | 12:00 PM | TCBD.3.03 | Mar 2 - May 17 |
| Thu | 3:00 PM | 4:00 PM | TCBD.3.03 | Mar 2 - May 17 |
NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for COMPX310 for more details
Indicative Fees for Machine Learning (COMPX310)
| Occurrence | Domestic | International | |
|---|---|---|---|
| Tuition | Resource | ||
| 20A (HAM) | $900 | $3824 | |
| 20A (TGA) | $900 | $3824 | |
Paper Outlines for Machine Learning (COMPX310)
The following paper outlines are available for Machine Learning (COMPX310).
If your paper occurrence is not listed contact the Faculty or School office.
Additional Information
Available Subjects: Applied Computing | Computer Science | Electrical and Electronic Engineering | Electronic Engineering | Mechatronics Engineering
Other available years: Machine Learning - COMPX310 (2021) , Machine Learning - COMPX310 (2019)
Paper details current as of : 9 July 2021 3:44pm
Indicative fees current as of : 31 July 2021 4:30am