Deep Learning and Machine Learning Concepts

What is Artificial Intelligence (AI) according to the Oxford Dictionary definition?

• The ability of machines to perform tasks that normally require human physical strength.

• The theory and development of computer systems able to perform tasks that normally require human intelligence.

• A fictional concept depicted in popular culture, like robots taking over the world.

• A system that can read human thoughts and predict future events.

How does Machine Learning relate to Artificial Intelligence?

• Machine Learning is an older technology that AI replaced.

• Machine Learning is a completely separate field from Artificial Intelligence.

• Machine Learning is a prominent subset of Artificial Intelligence.

• Artificial Intelligence is a subset of Machine Learning.

What is a key difference between Machine Learning and traditional programming?

• Traditional programming allows computers to learn from data, while Machine Learning requires explicit instructions.

• Machine Learning teaches computers to learn from data and make decisions without explicit programming for each task, unlike traditional programming.

• Traditional programming is used for complex tasks, while Machine Learning is only for simple tasks.

• Machine Learning systems are always faster than traditionally programmed systems.

When teaching a computer to recognize water bottles using Machine Learning, what approach is used?

• Manually coding specific rules for features like caps and straws.

• Showing the computer many pictures of water bottles and letting it identify patterns.

• Providing only one example and expecting the computer to generalize immediately.

• Giving the computer verbal instructions on what a water bottle looks like.

Which of the following are the three main types of Machine Learning mentioned in the video?

• Predictive learning, Analytical learning, Generative learning.

• Supervised learning, Unsupervised learning, Reinforcement learning.

• Explicit learning, Implicit learning, Adaptive learning.

• Rule-based learning, Pattern-based learning, Decision-based learning.

How does Deep Learning relate to Machine Learning?

• Deep Learning is a broader field that encompasses Machine Learning.

• Deep Learning is a specialized domain within Machine Learning.

• Deep Learning and Machine Learning are two entirely separate fields.

• Machine Learning is a specialized domain within Deep Learning.

What are the main components of a neural network's structure?

• Only an input layer and an output layer.

• An input layer, one or more hidden layers, and an output layer.

• A single layer of interconnected nodes.

• Only hidden layers and an output layer.

What is the defining characteristic of a deep learning algorithm in terms of its structure?

• It must have exactly three layers.

• It must have more than three layers.

• It must have fewer than three layers.

• The number of layers is irrelevant.

How do neural networks learn to distinguish features like different dog breeds?

• By randomly guessing until it gets the correct answer.

• By adjusting its connections (synapses) between nodes.

• By receiving direct programming instructions for each feature.

• By asking a human for clarification on each new input.

What is a key characteristic of the deep learning process regarding human involvement?

• It requires constant human supervision and intervention.

• It is entirely manual and human-driven.

• It is constitutionally automated, requiring minimal human intervention.

• It can only learn with direct human programming for every task.