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Machine Learning and AI Foundations: Decision Trees with KNIME

Suggested prerequisites

  • General familiarity with supervised machine learning
  • Understanding of terms such as target variable, input variable, algorithm, and train/test partition

Decision trees are transparent, available in every platform, and foundational to more advanced techniques like Random Forests and XGBoost. And if you’re a data scientist looking to pivot to machine learning, there’s arguably no better topic to kick off your learning journey. In this course, learn the essentials of machine learning pertaining to predictive analytics and working with decision trees. Along the way, instructor Keith McCormick provides demonstrations using the KNIME Analytics Platform, so you can grasp how these concepts work in real-world scenarios.

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