Final Exam: Low-code Machine Learning with KNIME

WHAT YOU WILL LEARN

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  Explore the knime workspace and sample workflows
  

  use one-hot and label encoding
  

  recall how regression models work
  

  perform one-hot and label encoding
  

  visualize aggregated data in scatter plots
  

  explore data attributes and compute correlations
  

  import csv data and compute summary statistics
  

  train an ensemble classifier
  

  improve model performance by standardizing data
  

  encode and split data for machine learning
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  detect and remove outliers
  

  standardize data to improve model performance
  

  oversample data to improve model performance
  

  process missing values and high-correlation attributes
  

  explore clustering models
  

  visualize clusters using scatter and box plots
  

  visualize data using moving averages
  

  perform time-series forecasting using arima
  

  recall how association rules mining works
  

  perform association rule learning for market basket analysis