Interesting. The pace of development in this field is such that practically every single book in Big Data landscape gets out of data before the ink dries on it :)
I concur that they serve as good reference for starters but in my opinion the best way to learn is to start from on-line docs (and these are pretty respectful when it comes to Spark) and progress from there. If you have a certain problem then put to this group and I am sure someone somewhere in this forum has come across it. Also most of these books' authors actively contribute to this mailing list. HTH Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com On 11 June 2016 at 16:10, Ted Yu <yuzhih...@gmail.com> wrote: > > https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8&qid=1465657706&sr=8-1&keywords=spark+mllib > > > https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8&qid=1465657706&sr=8-3&keywords=spark+mllib > > > https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8&qid=1465657706&sr=8-2&keywords=spark+mllib > > > On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel <deic...@gmail.com> wrote: > >> >> Hey >> >> Namaskara~Nalama~Guten Tag~Bonjour >> >> I am a newbie to Machine Learning (MLIB and other libraries on Spark) >> >> Which would be the best book to learn up? >> >> Thanks >> Deepak >> -- >> Keigu >> >> Deepak >> 73500 12833 >> www.simtree.net, dee...@simtree.net >> deic...@gmail.com >> >> LinkedIn: www.linkedin.com/in/deicool >> Skype: thumsupdeicool >> Google talk: deicool >> Blog: http://loveandfearless.wordpress.com >> Facebook: http://www.facebook.com/deicool >> >> "Contribute to the world, environment and more : >> http://www.gridrepublic.org >> " >> > >
