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Fundamentals of Machine Learning

Cost: $380 per participant

Learning Outcomes:

At the end of this workshop, participants should be able to:

  • Understand the big ideas of machine learning (e.g. supervised vs unsupervised machine learning)

  • Recognise the difference between bias and variance

  • Evaluate difference models in terms of metrics

  • Have an awareness of different machine learning techniques and interpret its output


Outline of Programme:

  • Supervised vs Unsupervised machine learning

  • Bias and Variance

  • Model evaluation metrics (e.g. accuracy, sensitivity, specificity)

  • K-nearest neighbour

  • K-means clustering

  • Decision Tree

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