About Machine Learning
Machine Learning
About this Collection
Machine learning is a subfield of Artificial Intelligence that uses data and statistical methods to train algorithms, so they can predict human behaviour.
Due to the recent technological advances, machine learning applications are used in many everyday activities, such as talking to your mobile phone (speech recognition), choosing a movie from a streaming service (recommendation engines), or using a self-driving car (computer vision).
The aim of this collection is to create a common space for researchers exploring different aspects of Machine Learning, including different methods and algorithms.
A non-exhaustive list of topics includes:
All article processing charges will be covered centrally by the European Commission.
Open Research Europe requires open access to research data supporting articles under the principle ‘as open as possible, as closed as necessary’. All articles should include citations to repositories that host the data underlying the results, together with any information needed to replicate, validate, and/or reuse the results/your study and analysis of the data. We recognise there may be exceptions due to ethical, data protection, or confidentiality considerations, or because the data have been obtained from a third party and access restrictions apply.
Due to the recent technological advances, machine learning applications are used in many everyday activities, such as talking to your mobile phone (speech recognition), choosing a movie from a streaming service (recommendation engines), or using a self-driving car (computer vision).
The aim of this collection is to create a common space for researchers exploring different aspects of Machine Learning, including different methods and algorithms.
A non-exhaustive list of topics includes:
- Supervised learning
- Unsupervised learning
- Semi-supervised learning
- Reinforcement learning
- Pattern recognition
- Natural language processing
- Machine Listening
All article processing charges will be covered centrally by the European Commission.
Open Research Europe requires open access to research data supporting articles under the principle ‘as open as possible, as closed as necessary’. All articles should include citations to repositories that host the data underlying the results, together with any information needed to replicate, validate, and/or reuse the results/your study and analysis of the data. We recognise there may be exceptions due to ethical, data protection, or confidentiality considerations, or because the data have been obtained from a third party and access restrictions apply.