18 Questions
What type of data can be expressed using decimals and fractions in supervised machine learning?
Quantitative data
In supervised machine learning, what type of data is counted using whole numbers (integers)?
Quantitative data
Which type of data in supervised machine learning has an order based on category?
Categorical data
What distinguishes quantitative data from qualitative data in supervised machine learning?
Qualitative data is grouped into categories with an order
Which type of data in supervised machine learning is critical to express accurately with decimals and fractions?
Quantitative data
How is supervised machine learning able to predict accurately based on past data?
By analyzing the features of past images and learning their associations
What is the slope (weight W) of the line described in the passage?
$2$
What is the y-intercept (bias B) of the line described in the passage?
$3$
What is the value of y when x is 10, according to the line equation given in the passage?
$19$
What are the initial guesses for the weight W and bias B in the machine learning approach described?
W = 10, B = 5
What is the purpose of the 'loss' mentioned in the machine learning approach?
All of the above
What is the key difference between traditional programming and machine learning approaches described in the passage?
Traditional programming involves creating rules, while machine learning involves guessing and optimizing parameters
What type of output variable is suitable for Classification in supervised learning?
Categorical data
In mail spam detection, what are some methods used to determine if an email is spam?
Reviewing the content, mail header, and checking for false information
What does Regression in supervised learning focus on?
Predicting real or continuous data
Which of the following is an example of a regression use case?
Predicting humidity based on temperature
What type of relationship exists between variables in a regression problem?
Linear relationship
How is the prediction of humidity based on temperature related to regression?
Humidity and temperature have a linear relationship in this case
Learn about the fundamentals of supervised machine learning, where machines learn under supervision by predicting with labeled datasets. Understand how computers 'guess', figure out the quality of the guess, optimize future guesses, and learn parameters for W and B.
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