In late June, I will be in New York to teach my 3-day workshop on Forecasting using R. Tickets are available at Eventbrite.
This is the first time I’ve taught this workshop in the US, having previously run it in the Netherlands and Australia. It will be based on the 2nd edition of my book “Forecasting: Principles and Practice” with George Athanasopoulos. All participants will get a print version of the book.
First semester teaching is nearly finished, and that means conference season for me. Here are some talks I’m giving in the next two months. Click the links for more details.
Melbourne, Australia. 28 May: Panel discussion: Forecasting models, the uncertainties and associated risk Boulder, Colorado, USA. 17-20 June: International Symposium on Forecasting. I’ll be talking about “Tidy forecasting in R”. New York, USA. 21 June: Feature-based time series analysis. New York Open Statistical Programming Meetup, eBay NYC.
For the last few years, I have been involved with running a 3-day short course on “Data Science for Managers”. We have run it twice each year since 2015, and it continues to prove very popular. We have some awesome presenters including Monash University professors Di Cook, Geoff Webb, and Kim Marriott, as well as several very experienced data scientists working in industry.
The next course will be held on 8-10 May 2018.
This week I have finished preliminary versions of two new R packages for time series analysis. The first (tscompdata) contains several large collections of time series that have been used in forecasting competitions; the second (tsfeatures) is designed to compute features from univariate time series data. For now, both are only on github. I will probably submit them to CRAN after they’ve been tested by a few more people.
tscompdata There are already two packages containing forecasting competition data: Mcomp (containing the M and M3 competition data) and Tcomp (containing the tourism competition data).
I have funding for a new post-doctoral research fellow, on a 2-year contract, to work with me and Professor Kate Smith-Miles on analysing large collections of time series data. We are particularly seeking someone with a PhD in computational statistics or statistical machine learning.
Experience with time series data. Experience with R package development. Familiarity with reproducible research practices (e.g., git, rmarkdown, etc). A background in machine learning or computational statistics.
Later this month I’m speaking at the 2017 Beijing Workshop on Forecasting, to be held on Saturday 18 November at the Central University of Finance and Economics.
I’m giving four talks as part of the workshop. Other speakers are Junni Zhang, Lei Song, Hui Bu, Feng Li and Yanfei Kang.
Full program details are available online.
I’m currently looking for a new research assistant to help (primarily) with some modelling and R coding as part of a project on forecasting mobile phone sales. The position is likely to last for about 6–9 months, and will be casual.
Requirements Based in Melbourne. I’d rather not communicate remotely. Able to work at least 20 hours per week. Some of that can be from home if necessary, but you do need to be at Monash University (Clayton campus) at least some of the time.
For a second year running, there will be another rOpenSci OzUnconference in Australia. This one will be held in Melbourne, on 26-27 October 2017.
Unlike regular conferences, there are no talks and there is no pre-determined agenda. It brings together scientists, developers, and open data enthusiasts from academia, industry, government, and non-profit to get together for a few days to work on R-related projects. The agenda is mostly decided during the conference itself, and involves participants dividing into small groups to work on the projects of most interest to them.
Last October I gave a 3-day masterclass on “Forecasting with R” in Eindhoven, Netherlands. There is a follow-up event planned for Tuesday 18 April 2017. It is particularly designed for people who attended the 3-day class, but if anyone else wants to attend they would be welcome.
Please register here if you want to attend.The preliminary schedule is as follows.
10.00 -- 11.00 New developments in forecasting using R forecast v8.
Last year we had WOMBAT (Workshop Organized by the Monash Business Analytics Team) at the zoo, and MeDaScIn (Melbourne Data Science Initiative) in the city.
This year we are combining forces to hold WOMBAT MeDaScIn 2017.
There will be four days of tutorials (Monday 29 May to Thursday 1 June), and the main conference on Friday 2 June. We have an impressive range of local and international presenters including Yihui Xie (author of Rmarkdown, Knitr, Bookdown, Blogdown and more), Di Cook (data visualization guru), Stephanie Kovalchik (Data Scientist at Tennis Australia), Amy Shi-Nash (Head of Data Science at Commonwealth Bank of Australia), Graham Williams (Director of Data Science at Microsoft) and many more.