Final Exam: No-code Machine Learning with RapidMiner

WHAT YOU WILL LEARN

• 

  List the features of rapidminer
  

  use univariate visualizations
  

  automate data preparation using the turbo prep tool
  

  use the auto model tool for automating machine learning
  

  partition data for machine learning
  

  encode data and select attributes
  

  use the turbo prep tool for automating data preparation
  

  prepare data using turbo prep
  

  assign roles to attributes
  

  compare two classification models
• 

  deploy a model to the local machine
  

  visualize data using bar charts and scatter charts
  

  perform k-means clustering
  

  describe what clustering is used for
  

  decompose time series data into trend, seasonal, and remainder components
  

  visualize time series differencing
  

  create and visualize moving averages
  

  forecast time series data with function and seasonal components
  

  outline what market basket analysis is used for
  

  validate arima forecasts