FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -Deep learning neural networks, or artificial neural networks, attempts to mimic the human brain through a combination of data inputs, weights, and bias. These elements work together to accurately recognize, classify, and describe objects within the data.

Detailed explanation-2: -Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

Detailed explanation-3: -A neural network is a network of artificial neurons programmed in software. It tries to simulate the human brain, so it has many layers of “neurons” just like the neurons in our brain. The first layer of neurons will receive inputs like images, video, sound, text, etc.

Detailed explanation-4: -Deep learning is an AI function that mimics the workings of the human brain in processing data for use in detecting objects, recognizing speech, translating languages, and making decisions. Deep learning is able to learn without human supervision, drawing from data that is both unstructured and unlabeled.

Detailed explanation-5: -Examples of various types of neural networks are Hopfield network, the multilayer perceptron, the Boltzmann machine, and the Kohonen network. The most commonly used and successful neural network is the multilayer perceptron and will be discussed in detail.