First of all we have to know that Machine Learning is part of Artificial Intelligence; as Tom Mitchel defined in his “Machine Learning” book “Machine Learning is the study of algorithms that allow computer programs to automatically improve through experience“. Machine Learning focuses most of the times on the study of Computational Complexity of the problems.
Machine Learning is applied in several areas, such as machine translation, automatic summarization or question-answering systems, and it is a good alternative to the manually built resources, since it can be improved at a lower cost and the guarantees are better. But linguistics may be in danger, for at this time more and more subtle specialist-reserved mathematical device are used.
In data analysis there are some systems that don’t need human intuition, but other systems are conceived so that the machine interacts with the expert. Nevertheless, human intuition is something that will always be needed, for the designer of the system is the one who decides and specifies the way information is represented and manipulated.
Artificial Intelligence has been created as the reflection of Natural Intelligence; intelligent behavior means that not always the reaction to a situation will be the same, what’s more, one of the qualities of intelligence is that behavior has not been programmed, but a computer only carries out something that has previously been programmed.
The algorithms that allow computers learn are classified based on the desired outcome of each algorithm, and Computational Learning Theory (a branch of Theoretical computer science) is responsible of its analysis.
The aim with Machine Learning is to make our life easier by doing programs that learn by themselves while they get experienced with the human, and are able to do common activities in a fast and effective way.
- Machine learning. (2009, June 3). In Wikipedia, The Free Encyclopedia. Retrieved 14:57, June 8, 2009, from http://en.wikipedia.org/w/index.php?title=Machine_learning&oldid=294182041
- Machine Learning. (2009). In Sheffield NLP. Retrieved 18:42, June 10, 2009, from http://nlp.shef.ac.uk/research/areas/nlp_ml.html
- Machine Learning. (2009, June 14). In ATALA, Association pour le Traitement Automatique des Langues. Retrieved 15:28, June 16, 2009, from http://www.atala.org/Machine-Learning-for-NLP
