After reading this post by Alex you will still just be talking about the weather, but you may have something interesting to say. 😉
Locating Mountains and More with Mahout and Public Weather Dataset by Alex Baranau
From the post:
Recently I was playing with Mahout and public weather dataset. In this post I will describe how I used Mahout library and weather statistics to fill missing gaps in weather measurements and how I managed to locate steep mountains in US with a little Machine Learning (n.b. we are looking for people with Machine Learning or Data Mining backgrounds – see our jobs).
The idea was to just play and learn something, so the effort I did and the decisions chosen along with the approaches should not be considered as a research or serious thoughts by any means. In fact, things done during this effort may appear too simple and straightforward to some. Read on if you want to learn about the fun stuff you can do with Mahout!
Tools & DataThe data and tools used during this effort are: Apache Mahout project and public weather statistics dataset. Mahout is a machine learning library which provided a handful of machine learning tools. During this effort I used just small piece of this big pie. The public weather dataset is a collection of daily weather measurements (temperature, wind speed, humidity, pressure, &c.) from 9000+ weather stations around the world.
What other questions could you explore with the weather data set?
The real power of “big data” access and tools may be that we no longer have to rely on the summaries of others.
Summaries still have a value-add, perhaps even more so when the original data is available for verification.