Boltzmann machines

A Boltzmann Machine is a type of artificial neural network that learns to model complex patterns in data. It consists of interconnected nodes, or neurons, that can be either “on” or “off.” By adjusting the connections based on examples, it aims to capture statistical relationships within the data. When given new inputs, it can generate similar outputs, making it useful for tasks like classification or generating new data. The machine gets its name from the physicist Ludwig Boltzmann, as it incorporates concepts from statistical mechanics to explore the probability of different states of the system.