What is the main difference between AI and Machine Learning?
a) AI refers to creating machines that can think like humans, while ML is a subset of AI that focuses on algorithms learning from data.
b) AI can only perform tasks manually, while ML cannot perform tasks without human input.
c) ML is a part of Artificial Intelligence that can learn without human intervention, but AI cannot.
d) There is no difference between AI and Machine Learning.
Which of the following is an example of Machine Learning?
a) A machine following pre-defined rules to play chess.
b) A self-driving car learning to drive based on real-world data.
c) A robot performing repetitive tasks.
d) A robot using a fixed algorithm to complete a task.
What is Deep Learning?
a) A subset of Machine Learning that uses multi-layered neural networks to model complex patterns.
b) A general term for intelligent systems that mimic human behavior.
c) A type of AI that is not related to Machine Learning.
d) A machine learning technique that doesn’t require data.
Which of the following is an example of Deep Learning?
a) Using decision trees to predict loan approvals.
b) Using neural networks for image recognition tasks.
c) A chatbot that uses predefined responses.
d) A regression model predicting sales based on historical data.
What does AI stand for?
a) Artificial Intelligence
b) Automated Input
c) Automated Intelligence
d) Artificial Input
What is supervised learning in Machine Learning?
a) A learning method where the system learns from labeled data with input-output pairs.
b) A learning method that requires no data to make predictions.
c) A learning method where the system adjusts based on feedback from the environment.
d) A learning method that uses no external information.
How does Deep Learning differ from Machine Learning?
a) Deep Learning requires labeled data, while Machine Learning doesn’t.
b) Deep Learning uses multi-layered neural networks, while Machine Learning uses simpler algorithms.
c) Machine Learning can handle only structured data, while Deep Learning handles unstructured data.
d) There is no difference; they are the same.
Which of the following is a key feature of AI systems?
a) The ability to think and reason like a human.
b) The ability to calculate fast without learning.
c) The ability to process only structured data.
d) The ability to perform tasks without human input.
What is the role of data in Machine Learning?
a) Machine Learning requires no data to function.
b) Machine Learning models use data to learn and make predictions.
c) Machine Learning uses data only for training purposes but not for predictions.
d) Machine Learning models are only concerned with processing data, not learning from it.
Which of the following is an application of Deep Learning?
a) Predicting the stock market using a decision tree.
b) Classifying images of animals using a neural network.
c) Using clustering algorithms to group customers.
d) Using linear regression to predict house prices.
Which is true about AI in general?
a) AI systems do not require human input once trained.
b) AI can perform tasks that typically require human intelligence, like visual perception and decision-making.
c) AI systems are always accurate and never make mistakes.
d) AI is only useful for games and entertainment.
Which of the following Machine Learning techniques is typically used for regression problems?
a) Convolutional Neural Networks
b) Linear Regression
c) Generative Adversarial Networks
d) Recurrent Neural Networks
Which of the following is the key difference between Supervised Learning and Unsupervised Learning in Machine Learning?
a) Supervised Learning uses labeled data, while Unsupervised Learning uses unlabeled data.
b) Supervised Learning requires no data, while Unsupervised Learning requires a lot of data.
c) Supervised Learning is for classification only, while Unsupervised Learning is for regression.
d) There is no difference between them.
What is the primary objective of reinforcement learning?
a) To classify data into categories based on labeled examples.
b) To generate new data that is similar to existing data.
c) To make decisions and take actions based on feedback to maximize rewards.
d) To cluster similar data points together.
Which technology is used for facial recognition systems?
a) Linear Regression
b) Convolutional Neural Networks
c) Decision Trees
d) K-Nearest Neighbors
Which of the following is an advantage of Deep Learning over Machine Learning?
a) Deep Learning models require less data to train.
b) Deep Learning can handle unstructured data, like images and audio, better than traditional ML.
c) Deep Learning models are always faster to train.
d) Deep Learning models have simpler architectures.
Which of the following tasks is more appropriate for Machine Learning than AI?
a) Autonomous driving
b) Image classification
c) Language translation
d) Playing chess
Which of the following Machine Learning models can be used for classification tasks?
a) Support Vector Machines
b) K-Means Clustering
c) Principal Component Analysis
d) Linear Regression
What type of problem is Deep Learning especially good at solving?
a) Linear equations
b) Image and speech recognition
c) Text-based data analysis
d) Predictive analytics for financial markets
How does a decision tree work in Machine Learning?
a) It makes decisions based on linear equations.
b) It splits data into subsets based on feature values.
c) It uses feedback from previous decisions to make choices.
d) It generates predictions using a neural network.
Which of the following best describes the “training” phase in Machine Learning?
a) The model tests predictions on new data.
b) The model learns from labeled data to improve its performance.
c) The model uses algorithms to predict the output.
d) The model stores data for later use.
What does the term “unsupervised learning” refer to?
a) The process of learning from labeled data.
b) The model is not provided with any data.
c) The model learns from data without labels or explicit instructions.
d) The model only learns from supervised feedback.
Which of the following best describes a neural network?
a) A computer program designed to play chess.
b) A model inspired by the brain’s structure that learns from data.
c) A decision-making process that uses pre-defined rules.
d) A machine learning technique used to solve optimization problems.
Which of the following is used to handle sequential data, such as speech or text?
a) Convolutional Neural Networks
b) Recurrent Neural Networks
c) Support Vector Machines
d) Random Forests
What does “generalization” mean in the context of Machine Learning?
a) The ability of a model to perform well only on the training data.
b) The ability of a model to make predictions on new, unseen data.
c) The ability to overfit the data.
d) The ability to process massive amounts of data at once.
Which is a key difference between Artificial Intelligence and Machine Learning?
a) AI is only about robotics, while ML is not.
b) AI involves creating systems that simulate human intelligence, while ML focuses on algorithms that learn from data.
c) AI requires no data to operate, while ML does.
d) AI can only perform tasks manually, while ML uses algorithms for automation.
