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| Description |
Statistical Reasoning
(Year: 2 Period: 5 Category: Compulsory )
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Course Objectives:
- 1. (understand)The student can explain basic concepts of probability and statistics with the aim of being able to apply statistical reasoning (including learning).
- 2. (understand)The student can explain important topics from (statistical) learning: regression (linear regression), classification (minimum error classifier, naive Bayesian classifier, linear discriminant classifiers, logistic regression, neural networks and support vector machines). Clustering (k-means) and dimensionality reduction (PCA).
- 3. (understand)The student can convert a mathematical formulation (particularly linear algebra) of a problem and solution into working software. Using the Python programming language and the Numpy/Scipy modules for efficient numerical programming.