News
NeurIPS 2020 Australia Pre-conference, Saturday 5th December 2020
The NeurIPS 2020 Australia Pre-conference will be held online on Saturday 5th December 2020, featuring 15 talks on computer vision and machine learning. A schedule and the zoom meeting link can be found at http://vision-learning.xyz/neurips2020/ |
AusDM 2020 Keynote Talks and Industry Showcase Virtual Event, 4 Dec - free of charge
Date and time: 1-4pm, Friday 4 December 2020, AEDT Cost: free of charge Venue: Online. A Zoom meeting link will be provided after registration. RSVP: https://www.eventbrite.com.au/e/ausdm2020-keynote-talks-and-industry-showcase-tickets-130976037855 Agenda: - 1-2pm: Keynote Talk 1 - 2-3pm: Keynote Talk 2 - 3-3:30pm: Industry Showcase Talk 1 - 3:30-4pm: Industry Showcase Talk 2
Keynote Talks Talk 1: Irrational Exuberance: Has Deep Learning Contributed anything to Time Series Data Mining? Speaker: Prof Eamonn Keogh Talk 2: Extraction of Hidden Information from Social Media Speaker: Prof Bela Stantic
Industry Showcase Talk 1: Deep Learning-Based Sensor Data Imputation System – A Case Study in Water Quality. Yi-Fan Zhang and Peter Thorburn. Speaker: Yi-Fan Zhang Talk 2: The Concept of an Analytics Shed. Garry Mitchell, Tony Nolan, Ed Lewis, Brian Benson, Peter Phillips and Warwick Graco. Speaker: Warwick Graco |
Free registration - IEEE DSAA, 6-9 Oct 2020
Free registration - the IEEE International Conference on Data Science and Advanced Analytics (DSAA), 6-9 Oct 2020. DSAA 2020 will be fully online. No registration fee is required for non-authors, but a complimentary registration is needed for joining the virtual conference sessions. See details at |
AusDM 2020 CFP: submission deadline extended to 22 August
AusDM 2020 Call for Papers: submission deadline extended to 22 August The Australasian Data Mining Conference (AusDM 2020) will run as a virtual conference in December. Industry showcase talks are welcome, as well as research and application papers. See details at https://ausdm20.ausdm.org |
Webinar: Missing Data Imputation Using Supervised Machine Learning
Topic: Missing Data Imputation Using Supervised Machine Learning Speaker: Marcus Suresh, Department of Industry, Science, Energy and Resources Date and time: 6-7pm Tuesday 28 July 2020, AEST Venue: Virtual via Zoom RSVP: https://www.meetup.com/CanberraDataSci/events/266992810/ After RSVP, please also register for the Zoom meeting under "Online event" in a right side panel on above webpage. Link to paper: https://link.springer.com/chapter/10.1007/978-3-030-35288-2_18 Link to PyImpuyte: https://pypi.org/project/PyImpuyte/ |
Coronavirus data analysis
A simple analysis of data around the Novel Coronavirus (COVID-19), to demonstrate data processing and visualisation with tidyverse and ggplot2. Download full analysis reports at links below. Coronavirus data analysis - China  |
CFP: IEEE DSAA 2020, due 24 May 2020
CFP: IEEE DSAA 2020 The 7th IEEE International Conference on Data Science and Advanced Analytics Sydney, Australia 6-9 October 2020 http://dsaa2020.dsaa.co/ Important dates: Paper Submission Deadline: 24 May 2020 Notification: 26 Jul. 2020 Camera Ready Due: 9 Aug. 2020 |
Call for Participation: AusDM 2019
The 17th Australasian Data Mining Conference (AusDM 2019) will be held in Adelaide, Australia, 2-5 December 2019. The Conference Program is now available at http://nugget.unisa.edu.au/AusDM2019/program.php, which features keynotes, tutorials and presentations on AI, data mining and machine learning. Registration of AusDM 2019 also gives access to the full program of the AI 2019 Conference. See registration details at http://nugget.unisa.edu.au/AusDM2019/registration.php |
G-NAF: over 13 million Australian addresses with geocodes
G-NAF is Australia’s authoritative, geocoded address file, containing than 13 million Australian physical address records with geocodes. It is produced by PSMA Australia Limited (PSMA), an unlisted public company formed by the nine governments of Australia to collate and standardise, format and aggregate location data from each of the jurisdictions into authoritative location based national datasets. |
A free online Deep Learning course by Google
A free online Deep Learning course, lectured by Vincent Vanhoucke, Principal Scientist at Google, and technical lead in the Google Brain team. Python is used for the course. You are expected to know basics of Python and machine learning (at least supervised learning) before attending the course. |
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