Speakers
Eduardo Fidalgo Fernández
Victor González-Castro
(University of León)
Description
In this course we will cover the basic concepts about machine learning with a theoretical and practical approach. Specifically, we will learn the concept of Machine Learning and Supervised Learning, a couple of classifiers (kNN and SVM) and how to evaluate them. Finally, we will learn how to create them in Python.
Objectives
- Comprehensive overview about machine learning basic concepts.
- Basic knowledge about how to evaluate classifiers’ performance and how to interpret its results
- Learn to build a simple classification experiment
Outcomes
- To know the basic knowledge about machine learning and supervised learning
- To know about two basic supervised learning classifiers: kNN and SVM
- To evaluate and interpret classification models’ results.
- To know the Google colab environment for computation in the cloud
- To build a simple classification experiment and assess its results.
Primary authors
Eduardo Fidalgo Fernández
Victor González-Castro
(University of León)
