Jeremy Howard gave a talk at the Melbourne R User Group on 16th March 2011.
Jeremy provided tips on how to successfully compete in data mining competitions. He showed how he combines R with other tools to build predictive models. He gave a walkthrough of the data, visualizations, and code, for a number of his competition entries. The talk also included an introduction to the theory behind Jeremy’s favourite modelling algorithm: random forests.
Discussions on various software tools (C, C++, Perl, Python, Unix shell, R, Matlab, SAS, SPSS, Excel, databases, Hadoop etc.) used in data analysis. Szilard Pafka (founder and co-organizer of the Los Angeles R users group) presents an overview and discusses the survey results regarding their usage by the members of the Los Angeles R users group. A plan for possible talks in the future (at LA RUG meetings) with more details on some of these tools and how they can be used with R is also discussed.
This presentation is aimed at all those working in commercial and government analytics, irrespective of what tools they use, and also to those students intending on such a career. R and other open source tools play a powerful, unique and disruptive role in business analytics, and are even now changing the landscape. The use of such tools leads to new business models and strategies that challenge the conventional approach.
The key element of the presentation is “Analyst First”, a new approach to analytics, where tools take a far less important place than the people who perform, manage, request or envision analytics, while analytics is a non-repetitive, exploratory and creative process where the outcome is not known at the start, and only a fraction of efforts are expected to result in success. This is in contrast with a common perception of analytics as IT and process.
During the first part of our meeting, Nicolas Christou gave an introduction of statistical finance in R, and presented a package he co-authored with previous PhD student David Diez (2010). Video of the talk is below:
During the second part, we accommodated shorter talks outlining R users’ experiences with statistical finance in R.
Kyle Matoba, a Finance PhD student from UCLA Anderson School of Management, presented on Algorithmic Trading with R.
Bryce Little, UCLA alum, presented on Constructing Minimum Variance Portfolios with R.