Diving into Data Science and Machine Learning with Big Data.......
5 Days effort, 40 GB RAM(REDHAT,Linux,5 Nodes Hadoop cluster on Openstack),500 GB HDD,20 GB retail data for buyers,2 Hive Joins(2.5 Hours run),Data conditioning,Normalization,SVMwithSGD(Support Vector Machine using Stochastic Gradient Descent.) with Spark MLIB,Distributed computation,20 Iterations for model building(1.5 Hours run),auROC: Double = 0.7858184517425998, Accuracy to predict repeat buyer is 78.58147387964868 %
Yeeeppeeeeeeeeeeeeeeeee!!!
P.S: Model is in scala so any scala or Java API can call it to get the prediction.
We鈥檝e updated our privacy policy so that we are compliant with changing global privacy regulations and to provide you with insight into the limited ways in which we use your data.
You can read the details below. By accepting, you agree to the updated privacy policy.
