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Guide to Model evaluation
First assignment: Python notebook for the assignment
First assignment: Python notebook for the assignment
First assignment: Python programming for feature extraction
Machine Learning I
The main goals of this course are: to introduce the basic concepts of Machine Learning and Big Data Machine Learning; to describe the main areas, techniques, ...
Course guide
Mandatory readings
En este apartado encontraremos enlaces a ficheros (HTML, PDF, Word...) de materiales de lectura de la asignatura, listado bibliográfico o enlaces web a ...
Exercises and projects
This section contains assignments to be carried out for this course.
Evaluation tests
Selfassessment, exams, and solutions.
Instructors
Instructors information
Syllabus
Syllabus de la asignatura: Temas que forman parte de la asignatura.
Lecture notes
This section contains the slides used during the lectures, each one with some orientation of what is explained in class.
Course introduction
Video de presentación de la asignatura.
Labs exercises
This section includes lab exercises to be carried out by the student. It uses Jupyter notebooks that must be followed step by step.
Related resources
This section contains materials and links to additional material.
Model evaluation
Lecture slides
Automated Planning
The course on Automated planning introduces the Artificial Intelligence approach to the planning task. Automated planning is a computational task that, given a ...
Learning guide
Other resources
Lecturers
Programme
Course programme
Learning
Slides on machine learning applied to planning
Bibliography (mandatory)
Class material
Download this Course
Download this Course