Aprendizagem Automática

Knowledge

• Understand the paradigms and challenges of Machine Learning, distinguishing Supervised, and Unsupervised learning.
• Learn the fundamental methods and their applications in data oriented knowledge discovery. Understand data features, the selection of models and their complexity.
• Understand the advantages and disadvantages of the different methods.

Applications

• Implement and adapt Machine Learning algorithms;
• Model real data experimentally.
• Interpret and evaluate experimental results.
• Validate and compare different Machine Learning algorithms.

Soft Skills

• Evaluate the suitability of each method to concrete applications and data sets.
• Critical evaluation of the results.
• Autonomy and self-reliance in the application and further studies in Machine Learning.