Data Science Final Exam Questions with 100%
Verified Answers
Why type of loss function is most common? - ✔️✔️Ordinary Least Function
(Squared Error). Motivated by normal distribution, easily computed & small
errors. The L1 loss is more robust to outliers.
Do you want high or low RMSE - ✔️✔️Want low rmse
What is R2 - ✔️✔️The coefficient of determination. Measures the proportion of
variability in y that can be explained using x
Do you want a high or low R2 - ✔️✔️High R2
What does TSS measure? - ✔️✔️The total variance in the response y
Surprise - ✔️✔️The inverse of probability
3 Main Steps of Machine Learning - ✔️✔️1. Model parameters in an array
2. Update the parameters over time by calc. gradient of the loss function
3. Changing paramters, minimize surprise.
Sample Space - ✔️✔️a set of all possible events
Event - ✔️✔️Subset of a sample space. Probability between 0 and 1
, Discrete Random Variables - ✔️✔️Taken values from a countable set
PMF - Probability Mass Function - ✔️✔️The resulting probability
CDF - Cumulative Distribution Function - ✔️✔️Probability that random variable X is
less than or equal to x.
What types of functions can discrete variables have? - ✔️✔️PMF & CDF
What type of functions can continuous variables have? - ✔️✔️PDF & CDF
PDF - Probability Density Function - ✔️✔️Percentage of distribution that falls
between 2 criteria
What does higher density mean in PDF & CDF? - ✔️✔️Higher Gradient
How do you get CDF from PDF? - ✔️✔️Take the integral of PDF
Joint Distribution - ✔️✔️When 2 variables come together as a pair.
Marginal Distributions - ✔️✔️If X is ignored, it is the distribution of Y.
Verified Answers
Why type of loss function is most common? - ✔️✔️Ordinary Least Function
(Squared Error). Motivated by normal distribution, easily computed & small
errors. The L1 loss is more robust to outliers.
Do you want high or low RMSE - ✔️✔️Want low rmse
What is R2 - ✔️✔️The coefficient of determination. Measures the proportion of
variability in y that can be explained using x
Do you want a high or low R2 - ✔️✔️High R2
What does TSS measure? - ✔️✔️The total variance in the response y
Surprise - ✔️✔️The inverse of probability
3 Main Steps of Machine Learning - ✔️✔️1. Model parameters in an array
2. Update the parameters over time by calc. gradient of the loss function
3. Changing paramters, minimize surprise.
Sample Space - ✔️✔️a set of all possible events
Event - ✔️✔️Subset of a sample space. Probability between 0 and 1
, Discrete Random Variables - ✔️✔️Taken values from a countable set
PMF - Probability Mass Function - ✔️✔️The resulting probability
CDF - Cumulative Distribution Function - ✔️✔️Probability that random variable X is
less than or equal to x.
What types of functions can discrete variables have? - ✔️✔️PMF & CDF
What type of functions can continuous variables have? - ✔️✔️PDF & CDF
PDF - Probability Density Function - ✔️✔️Percentage of distribution that falls
between 2 criteria
What does higher density mean in PDF & CDF? - ✔️✔️Higher Gradient
How do you get CDF from PDF? - ✔️✔️Take the integral of PDF
Joint Distribution - ✔️✔️When 2 variables come together as a pair.
Marginal Distributions - ✔️✔️If X is ignored, it is the distribution of Y.
