Understanding Supervised and Unsupervised Learning

What are the three main types of learning discussed in the context of Artificial Intelligence?

• Reinforcement, Unsupervised, and Supervised

• Observational, Experimental, and Theoretical

• Cognitive, Behavioral, and Social

• Memorization, Practice, and Application

Which type of learning involves an AI adapting its behavior based on feedback from its environment, similar to how a baby learns to walk?

• Unsupervised Learning

• Supervised Learning

• Reinforcement Learning

• Passive Learning

What is the primary characteristic of unsupervised learning?

• It requires a supervisor to provide correct answers.

• It involves learning through feedback from an AI's behavior.

• It is the process of learning without training labels.

• It focuses on classifying data into predefined categories.

In supervised learning, what role does a "supervisor" play?

• It provides the AI with new, unlabeled data.

• It helps the AI adapt its behavior through trial and error.

• It points out mistakes and provides correct answers during the learning process.

• It compresses data to allow for faster streaming.

Which of the following is an example of supervised learning in everyday life?

• A baby learning to walk by practicing and balancing.

• YouTube recommending videos based on viewing patterns.

• An email account classifying a message from your boss as important or spam.

• An AI learning to play a game by receiving rewards for good moves.

What biological structure primarily inspired early computer scientists in creating artificial intelligence?

• The human eye

• Neurons in the brain

• The heart's pumping action

• DNA strands

What was the name of the machine built by Frank Rosenblatt in 1958 to classify images as triangles or not triangles?

• The Analyzer

• The Classifier

• The Perceptron

• The Cognitron

How did the Perceptron learn to improve its classification accuracy?

• By randomly guessing until it got the correct answer.

• By receiving new images without any feedback.

• By adjusting the electricity crossing its synapses and its threshold levels based on correct/incorrect classifications.

• By being reprogrammed manually for each new image.

What is the primary function of a perceptron in classifying items like bagels and donuts?

• To randomly assign labels to items.

• To take inputs, multiply them by weights, sum them, and compare to a bias.

• To visually inspect items and make a guess.

• To store data about items without processing.

In a perceptron model, what does the "bias" represent?

• The initial random guess of the perceptron.

• The final output of the classification.

• A threshold that determines the neuron's firing or classification.

• The sum of all weighted inputs.