Quiz 1

False

Regression and Classification methods are different types of Reinforcement learning! True False

Database management

Which of the following is NOT a common application of machine learning? Database management Fraud detection Image classification Customer segmentation

the machines learn to model relationships based on labeled data!

Which one is correct definition of Supervised learning? In supervised learning ------- the machines learn to model relationships based on labeled data! the machines are not given labeled data the machines learn from interacting with its environment by producing actions and discover rewards

True

The goal of unsupervised learning is to discover the underlying patterns and find groups of samples that behave similarly! True False

AI is concerned with understanding and replicating human intelligence, while ML is concerned with making predictions using data, and DL is concerned with finding patterns in data

Which of the following best describes the main difference between AI, ML, and DL? AI is concerned with understanding and replicating human intelligence, while ML is concerned with making predictions using data, and DL is concerned with finding patterns in data ML is concerned with understanding and replicating human intelligence, while AI is concerned with making predictions using data, and DL is concerned with finding patterns in data DL is concerned with understanding and replicating human intelligence, while ML is concerned with making predictions using data, and AI is concerned with finding patterns in data AI is concerned with finding patterns in data, while ML is concerned with understanding and replicating human intelligence, and DL is concerned with making predictions using data

Machine learning is concerned with making predictions using data, while statistical learning is concerned with understanding the underlying relationship of the data

Which of the following best describes the main difference between statistical learning and machine learning? Machine learning is concerned with making predictions using data, while statistical learning is concerned with understanding the underlying relationship of the data Statistical learning is concerned with making predictions using data, while machine learning is concerned with understanding the underlying relationship of the data Statistical learning relies on mathematical models and assumptions, while machine learning does not Machine learning relies on mathematical models and assumptions, while statistical learning does not

Compiler learning

Which of the following is NOT a type of machine learning? Supervised learning Unsupervised learning Compiler learning Reinforcement learning

Constructing super complex models for maximum predictability

Which of the following is typically NOT a goal of statistical learning? Understanding the relationships between variables in a dataset Predicting the value of a target variable based on the values of other variables Finding patterns in data Constructing super complex models for maximum predictability

All of the above

Which one is correct about machine learning? Subset of AI that enables computers to learn from data. the model is trained with a set of algorithms A machine learning system is trained (with algorithms) rather than explicitly programmed ML involves automated detection of meaningful patterns in data and apply the pattern to make predictions on unseen data All of the above