Implement a Big Data Math Algorithm in 2hrs - Linear Regression

We will take a simple yet popular & powerful math algorithm such as Linear Regression and implement a distributed version in 2hrs.

Pre-requisites: Knowledge of Java or R

See: http://h2o.0xdata.com/

Warning: Only software programmers ignore Warnings! :)

That said, this seriously is a very hands on java-intense exercise. Extinguished engineers may not enjoy the proceedings.

Patrons need to ensure that the following steps have been achieved before hand:

1. Downloaded the H2O source from: https://github.com/0xdata/h2o
like so,

$ git clone https://github.com/0xdata/h2o.gi...

2. Installed IntelliJ or eclipse on your laptop.

3. Imported project into IDE (by pointing to h2o directory)

4. Run main in water.Boot within IDE
(This should launch H2O within IDE)

5. Try out the following samples -

https://github.com/0xdata/h2o/tree/master/src/samples/java/water

6. New documentation will be added to http://docs2.0xdata.com/

This session will be hands-on: Hacking & less of a spectator sport.

This session will expose user to concepts of Distributed Fork / Join and working with a consistent Distributed K/V Store and Math-hacking over simplest Map & Reduce concepts, as well as DRemoteTask.

Finally Our API is still being morphed & some of the boilerplate will go away & get a bit easier in time.

Hoping to see the hacker in you.

[ Makers should kindly accept our sincere apology for rescheduling the event due to difficulty grabbing a venue for the size in SF. We are committed to doing more events in SF in this and months ahead.]