I read Lyubimov's and Palumbo's book on Mahout Samsara up to chapter 4 ( Distributed Algebra ). I have some familiarity with R, I did study linear algebra and calculus in undergrad. In my master's I studied statistical pattern recognition and researched a number of ML algorithms in my thesis - spending more time on SVMs. This is to ask: what is the learning curve of Samsara? How complicated is to work with distributed algebra to create an algorithm? Can someone share an example of how long she/he took to go from algorithm conception to implementation?
Thanks Gustavo
