This is the last of the exercise set on H2O’s machine learning algorithms. Please do them in sequence. This requires some additional data. I have provided the links, so please download them when it’s needed. Answers to the exercises are available here. Please check the documentation before starting this exercise set. For other parts of […]
h2o
Machine Learning With H2O Part 3 Solutions
Below are the solutions to these exercises on h2o and machine learning ############### # # # Exercise 1 # # # ############### setwd("H20/") library(h2o) cluster.h <- h2o.init() bank_data <- h2o.importFile("data\bank.csv") response = "y" predictors <- c("age","job","marital","education","default","balance","housing","loan") splits <- h2o.splitFrame(bank_data,c(0.8,0.1)) train <- splits[[1]] valid <- splits[[2]] test <- splits[[3]] gbm.m <- h2o.gbm(x, y, train, nfolds = […]
Machine Learning With H2O – Part 2: Exercises
In this Exercise set ,we will continue our journey with H20’s Machine Learning algorithms. We will also find out about Gradient Boosted Machine and Classifiers like naive bayes. On the next series, we will conclude the machine learning journey with H2O. Answers to the exercises are available here. Please check the documentation before starting this […]
Applying Machine Learning with H2O Exercises
In this Exercise set we will see how to work with h2o’s main machine learning algorithms and their parameters download the Energy efficiency dataset from UCLA data repository and lets get started . Answers to the exercises are available here. Please check the documentation before starting this exercise set. Exercise 1 Load the data in […]
Big Data Analytics in H20 Exercises (Part -2)
In the last set of exercises, you have seen the basic functionalities of H2O. In this exercise set, we will explore H2O further and see how to wrangle data in H2O. Answers to the exercises are available here. Please check the documentation before starting this exercise set. If you obtained a different (correct) answer than […]
Big Data Analytics with H20 in R Exercises -Part 1
We have dabbled with RevoScaleR before , In this exercise we will work with H2O , another high performance R library which can handle big data very effectively .It will be a series of exercises with increasing degree of difficulty . So Please do this in sequence . H2O requires you to have Java installed […]