Statistics and Mathematics for NLP
General details of the subject
- Face-to-face degree course
Description and contextualization of the subjectIntroduction to basic concepts of statistics in the field of natural language processing. Inferential aspects will be worked on, including the most common statistical tests, as well as interval estimation. Furthermore, basic concepts of functions and linear algebra will be introduced for Natural Language Processing tasks with the final aim of gaining understanding of the rationale behind neural networks.
|EZEIZA RAMOS, NEREA||University of the Basque Country||Profesorado Agregado||Doctor||Bilingual||Computer Languages and Systemsfirstname.lastname@example.org|
|IRIGOYEN GARBIZU, ITZIAR||University of the Basque Country||Profesorado Agregado||Doctor||Bilingual||Science of Computation and Artificial Intelligenceemail@example.com|
|Ability to understand and apply the appropriate statistical tests according to the objectives set, given a set of data.||35.0
|Ability to understand basic mathematical language.
|Ability to understand the underlying intuition in vector spaces and perform basic calculations.||40.0
|Type||Face-to-face hours||Non face-to-face hours||Total hours|
|Applied computer-based groups||20||30||50|
|Name||Hours||Percentage of classroom teaching|
|Prácticas con ordenador, laboratorio, salidas de campo, visitas externas||50.0||40
|Name||Minimum weighting||Maximum weighting|
|Attendance and participation||10.0
Learning outcomes of the subjectPose the correct hypotheses according to the objectives and characteristics of the data to perform statistical tests.Interpret the results of a statistical test and complement it with estimation by intervals.Know the definition of what a function is. Know the concept of derivative. Perform basic calculations of linear algebra.Learn to use specific software to perform calculations related to natural language processing tasks.
Ordinary call: orientations and renunciationFinal exam to assess the subject.
Extraordinary call: orientations and renunciationFinal exam to assess the subject.
Temary1. Introduction to hypothesis testing: independence test, Mc Nemar test
2. Real function. Concept of derivative
3. Matrix calculus
Basic bibliographyR.H. Baayen (2008). Analyzing Linguistic Data. A Practical Introduction to Statistics using R. Cambridge University Press
G. Strang (2019). Linear Algebra and Learning from Data. Cambridge University PressA. Trask (2019). Grokking deep learning. Manning Publications Co.