Hamishmar

Aprendizaje Automático

“Aprendizaje Automático” translates to “Machine Learning” in English. It is a subset of artificial intelligence that focuses on the development of algorithms and statistical models that enable computers to perform specific tasks without explicit instructions. Instead, machine learning systems use patterns and inference derived from data, allowing them to improve their performance on tasks over time as they are exposed to more data.

Machine learning is broadly categorized into three types: supervised learning, where the model learns from labeled training data; unsupervised learning, where the model identifies patterns in data without predefined labels; and reinforcement learning, where an agent learns to make decisions by receiving feedback from its actions in an environment.

Applications of machine learning include natural language processing, image and speech recognition, recommendation systems, and predictive analytics, among many others. Overall, machine learning is a critical technology driving advancements in various fields, enabling computers to learn from and adapt to new information.