Machine learning in R

Machine learning in R

Training description

Machine Learning changes the business reality rapidly. Solutions that is being built based on data, may support the decision-making process.

“Machine Learning in R”  is an advanced training on building predictive analytics in R.

Duration: 3 days 8 hours each (including an hour lunch break)

Extended version is also available – 4 days 8 hours each.

Requirements: knowledge of R programming language at an intermediate level which can be acquired during our training “Introduction to R”.

Training agenda

Part one: Let’s get it started!

  • What’s Machine Learning?
  • Algorithm distinction
  • Machine Learning workflow

Part two: The necessary foundation

  • Training data vs.Test data
  • Exploratory Data Analysis
  • Feature selection/extraction
  • Overfitting
  • Model validation

Part three: Overview of algorithms

  • Statistical modeling recap (linear regression, logistic regression)
  • Decision trees
  • SVM
  • Ensemble methods
    • Random Forest
    • Boosting

Part four: In search of best solution…

  • Dimensionality reduction techniques
  • Regularization
  • Hyperparameter tuning
  • Black-box model interpretability

Upcoming open trainings

Currently, no open training covering the given issue is planned. We encourage you to contact us regarding the closed training.

Contact us about closed training
Go to open training base

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