Description: The newer predictive modeling tools are powerful but they work best when supported by a lot of computing power. Parallel processing is very powerful but often very difficult to implement. Dihui and Richard take us through the maze of options with H2O, SparkNet/MLib and Mahout. Which do you use for a generalized linear model (GLM), and which is better for high-volume data manipulation?

Description: In this article, we are going to discuss the AR model by making connections to time-dependent ordinary differential equations.

Description: Spark offers a way to get some dramatic speed and scalability advantages over the Map-reduce methodology whenever you are doing iterative data processing and particularly when you want interactive data analysis capability. Find out why “lazy execution” can be a desirable characteristic when dealing with big data.