ISLA IPGT 24863

Introduction to Machine Learning in R

• ApresentaçãoPresentation

  This curricular unit aims to present the main concepts and methodologies of machine learning, supported by programming in R. Machine learning is a field of artificial intelligence that uses algorithms to find patterns, extract knowledge, and build predictive models from data. It is a data analysis approach that involves the construction and adaptation of computational models, allowing programs to "learn" from data in order to improve their ability to infer knowledge, make predictions and support decision making. R is a programming language and statistical software, popular among analysts and data scientists, and widely used for data analysis and visualization. In this curricular unit, students will use the R language to perform common machine learning tasks, such as data pre-processing, exploratory data analysis, building and tuning models, and evaluating results.
• ProgramaProgramme

  Machine Learning Concepts Supervised Learning Regression Linear Regression Time Series Analysis (Forecasting): ARIMA Classification Tree-based models (Decision Trees, Random Forests) Support Vector Machines (SVM) Naive Bayes Classifier (NB) K-Nearest Neighbors (KNN) Unsupervised Learning Dimensionality Reduction Principal Components Analysis (PCA) Clustering K-means Hierarchical Clustering Association Rules Apriori
• ObjectivosObjectives

  At the end of this course, students will be able to: Know the basic concepts of machine learning Explain the main types and applications of machine learning Use the R language to manipulate data and build models Apply various machine learning algorithms to solve real-world problems Evaluate and compare the performance of different machine learning models Interpret and communicate results from machine learning models
• BibliografiaBibliography

  James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R. Springer Science & Business Media. ISBN 9781461471370  Burger, S. V. (2018). Introduction to Machine Learning with R: Rigorous Mathematical Analysis. O'Reilly Media, Inc. ISBN 9781491976449 Lantz, B. (2019). Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition. Packt Publishing. ISBN 9781788295864
• MetodologiaMethodology

  Within the scope of this curricular unit, students will have the opportunity to apply the knowledge transmitted throughout different modules and apply them to solve practical problems using real data from different areas of business activity (retail, banking, marketing, health, etc).
• LínguaLanguage

  Português
• TipoType

  Anual
• ECTS

  4
• NaturezaNature

  Mandatory
• EstágioInternship

  Não