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MAI4CAREU - Machine Learning: Model Evaluation and Improvement

MAI612 Lecture 5 equips students with a concise yet comprehensive toolkit for evaluating and enhancing machine learning models, fostering a deep understanding of the intricacies involved in the process.

The University of Cyprus's MSc Artificial Intelligence is part of the Master programme in Artificial Intelligence 4 Careers in Europe (MAI4CAREU). One of Master's programme's courses, MAI612 - Machine Learning is split up into several lectures. Taught by Vassilis Vassiliades, PhD, the fifth lecture of the MAI612 - Machine Learning course focuses on Model Evaluation and Improvement.

Learning outcomes

  • The issue of generalization in machine learning and how it is related to model evaluation
  • The concepts of overfitting, underfitting and the bias-variance tradeoff
  • The importance of training, validation and test setswhat k-fold cross-validation is and when to use it
  • When to acquire more data to improve ML models
  • How to improve ML models using L1 and L2 regularization
  • How to improve ML models by tuning their hyperparameters 

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Additional information

Target audience
Digital skills for ICT professionals and other digital experts.
Geographic scope - Country
Austria
Belgium
Bulgaria
Cyprus