Solution

The correct answer is All the statements are correct.

Key Points

•  A. "It is essentially a machine learning algorithm." 
  • This is true because artificial neural networks (ANNs) are indeed a type of machine learning algorithm. These are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a type of machine perception, labeling or clustering raw input.
• B. "It is useful when solving the problems for which the data set is very large." 
  • Again, this is true. ANNs have proven highly useful in situations where the dataset is large and complex, as they can learn directly from the data and make predictions or classifications.
• C. "They are able to extract features without input from the programmer." 
  • This is also true. One of the significant strengths of ANNs is their ability for feature learning or automatically discovering the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task.
• D. "These are systems modeled on the human brain and nervous system." 
  • This is correct as well. ANNs indeed take inspiration from the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely mirror the neurons in a biological brain. Each connection can transmit a signal from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it.