Foundations of Machine Learning

Question 1

What is the primary focus of Statistical Machine Learning?

Answer 1

Statistical Machine Learning focuses on understanding the underlying statistical properties of data and making inferences based on these properties.

Question 2

What is the main objective of Classical Machine Learning?

Answer 2

The main objective of Classical Machine Learning is to develop algorithms that can learn from and make predictions based on data.

Question 3

True or False: Statistical ML relies heavily on probability theory.

Answer 3

True

Question 4

Fill in the blank: In Statistical ML, the model is often built through __________ methods.

Answer 4

inferential

Question 5

Which type of machine learning is typically concerned with feature engineering?

Answer 5

Classical Machine Learning

Question 6

What is a key characteristic of Classical ML algorithms?

Answer 6

They often require extensive feature extraction and manual tuning.

Question 7

Multiple Choice: Which technique is commonly used in Statistical ML for parameter estimation? A) Gradient Descent B) Maximum Likelihood Estimation C) Decision Trees

Answer 7

B) Maximum Likelihood Estimation

Question 8

What is one application of Statistical ML in real-world scenarios?

Answer 8

Statistical ML is often used in fields like epidemiology for understanding disease spread.

Question 9

True or False: Classical ML techniques are generally more flexible than Statistical ML techniques.

Answer 9

False

Question 10

Fill in the blank: __________ is a common application area for Classical Machine Learning.

Answer 10

Computer Vision

Question 11

What is a common algorithm used in Classical ML for classification tasks?

Answer 11

Support Vector Machines (SVM)

Question 12

Multiple Choice: Which of the following is NOT a focus area of Statistical ML? A) Hypothesis Testing B) Predictive Modelling C) Image Recognition

Answer 12

C) Image Recognition

Question 13

What type of data is often analyzed using Statistical ML?

Answer 13

Structured data with known distributions.

Question 14

True or False: Statistical ML can be used for both supervised and unsupervised learning.

Answer 14

True

Question 15

Fill in the blank: __________ is a popular application of Statistical ML in the finance sector.

Answer 15

Risk assessment

Question 16

What is a major limitation of Classical ML?

Answer 16

It often requires a large amount of labeled data for training.

Question 17

Multiple Choice: Which of the following fields primarily applies Statistical ML? A) Natural Language Processing B) Video Games C) Climate Modeling

Answer 17

C) Climate Modeling

Question 18

What is the role of hypothesis testing in Statistical ML?

Answer 18

Hypothesis testing is used to determine if observed patterns in data are statistically significant.

Question 19

True or False: Classical ML techniques are typically less interpretable than Statistical ML techniques.

Answer 19

False

Question 20

Fill in the blank: __________ is a common evaluation metric used in Classical ML.

Answer 20

Accuracy

Question 21

What is an example of a task that can be performed using Statistical ML?

Answer 21

Estimating the average treatment effect in clinical trials.

Question 22

What is the primary data type used in Natural Language Processing (NLP)?

Answer 22

Text data

Question 23

Multiple Choice: Which of the following is a common application of Classical ML in NLP? A) Sentiment Analysis B) Word Embeddings C) Topic Modeling

Answer 23

A) Sentiment Analysis

Question 24

True or False: Statistical ML models can handle missing data more effectively than Classical ML models.

Answer 24

True

Question 25

What is a common challenge faced by both Statistical and Classical ML?

Answer 25

Overfitting to training data.

Question 26

Fill in the blank: __________ models are often preferred in Statistical ML for their robustness to outliers.

Answer 26

Bayesian

Question 27

What is a key advantage of Statistical ML over Classical ML?

Answer 27

Statistical ML can provide more insight into the uncertainty of predictions.

Question 28

Multiple Choice: Which of the following is a method used in Classical ML for dimensionality reduction? A) Principal Component Analysis B) Bayesian Inference C) Regression Analysis

Answer 28

A) Principal Component Analysis

Question 29

What is a primary goal of machine learning in computer vision?

Answer 29

To enable computers to interpret and understand visual information from the world.

Question 30

True or False: Both Statistical ML and Classical ML can be applied to the same problem but may yield different insights.

Answer 30

True