Artificial neural networks (ANNs) are a specific class of machine learning models inspired by the structure of the human brain. They consist of interconnected ‘neurons’ arranged in layers. Machine learning (ML) is a subfield of artificial intelligence in which algorithms learn patterns from data to make predictions or decisions, rather than following hand-coded rules. Machine learning is a subfield of artificial intelligence in which computers learn to perform tasks without being explicitly programmed for every single action. Instead of rigid rules, machines analyse large amounts of data, recognise patterns, relationships and structures within it, and improve their performance based on these experiences. Artificial neural networks (ANNs) are algorithms inspired by the functioning of the human brain. They form the backbone of machine learning and deep learning. By recognising complex patterns in large amounts of data, they enable a wide range of applications.
Les réseaux neuronaux artificiels (RNA) sont des algorithmes inspirés du fonctionnement du cerveau humain. Ils constituent la colonne vertébrale de l’apprentissage automatique et du deep learning. En identifiant des modèles complexes dans de grands volumes de données, ils permettent de nombreuses applications.
