Machine Learning (Stanford) Coursera (Week 1, Quiz 1) for the github repo: https://github.com/mGalarnyk/datasciencecoursera/tree/master/Stanford_Machine_Learning

machineLearningWeek1Quiz1.md

Machine Learning Week 1 Quiz 1 (Introduction) Stanford Coursera

Github repo for the Course: Stanford Machine Learning (Coursera)

Question 1

A computer program is said to learn from experience E with

respect to some task T and some performance measure P if its

performance on T, as measured by P, improves with experience E.

Suppose we feed a learning algorithm a lot of historical weather

data, and have it learn to predict weather. What would be a

reasonable choice for P?

• The probability of it correctly predicting a future date's weather.

• None of these.

• The weather prediction task.

• The process of the algorithm examining a large amount of historical weather data.

Answer:

The probability of it correctly predicting a future date's weather.

Question 2

Suppose you are working on weather prediction, and use a

learning algorithm to predict tomorrow's temperature (in

degrees Centigrade/Fahrenheit).

Would you treat this as a classification or a regression problem?

• Regression

• Classification

Answer:

Regression

Question 3

Suppose you are working on stock market prediction. You would like to predict whether or not a certain company will declare bankruptcy within the next 7 days (by training on data of similar companies that had previously been at risk of bankruptcy). Would you treat this as a classification or a regression problem?

• Regression

• Classification

Answer:

Classification

Question 4

Some of the problems below are best addressed using a supervised

learning algorithm, and the others with an unsupervised

learning algorithm. Which of the following would you apply

supervised learning to? (Select all that apply.) In each case, assume some appropriate

dataset is available for your algorithm to learn from.

• Examine a web page, and classify whether the content on the web page should be considered "child friendly" (e.g., non-pornographic, etc.) or "adult."

• Given data on how 1000 medical patients respond to an experimental drug (such as effectiveness of the treatment, side effects, etc.), discover whether there are different categories or "types" of patients in terms of how they respond to the drug, and if so what these categories are.

• In farming, given data on crop yields over the last 50 years, learn to predict next year's crop yields.

• Given a large dataset of medical records from patients suffering from heart disease, try to learn whether there might be different clusters of such patients for which we might tailor separate treatments.

Answer:

True or False	Statement
True	Examine a web page, and classify whether the content on the web page should be considered "child friendly" (e.g., non-pornographic, etc.) or "adult."
True	In farming, given data on crop yields over the last 50 years, learn to predict next year's crop yields.

Question 5

Which of these is a reasonable definition of machine learning?

• Machine learning is the field of allowing robots to act intelligently.

• Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed.

• Machine learning learns from labeled data.

• Machine learning is the science of programming computers.

Answer:

Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed.

all answers are wrong

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