MACHINE LEARNING
106403Module 1: Introduction
Q1a. (a) Who is called the father of Machine Learning? (i) Geoffrey Hill (ii) Geoffrey Chaucer (iii) Geoffrey Everest Hinton (iv) Tom Mitchell20232m
Module 1: Introduction
View this question on its own page →(a) Who is called the father of Machine Learning?
(i) Geoffrey Hill
(ii) Geoffrey Chaucer
(iii) Geoffrey Everest Hinton
(iv) Tom MitchellQ1a. Which of the following is correct use of cross validation? (i) Selecting variables to include in a model (ii) Comparing predictors (iii) Electing parameters in prediction function (iv) All of the above20222m
Module 1: Introduction
View this question on its own page →Which of the following is correct use of cross validation?
(i) Selecting variables to include in a model
(ii) Comparing predictors
(iii) Electing parameters in prediction function
(iv) All of the aboveQ1b. Which of the following statement(s) is/are true for Gradient Decent (GD) and Stochastic Gradient Decent (SGD)? (1) In GD and SGD, you update a set of parameters in an iterative manner to function. minimize the error (2) In SGD, you have to run through all the samples in your training set for a single update of a parameter in each iteration. (3) In GD, you either use the entire data or a subset of training data to update a parameter in each iteration. (i) Only (1) (ii) (1) and (2) only (iii) (3) and (2) only (iv) (1), (2) and (3)20222m
Module 1: Introduction
View this question on its own page →Which of the following statement(s) is/are true for Gradient Decent (GD) and Stochastic Gradient Decent (SGD)?
(1) In GD and SGD, you update a set of parameters in an iterative manner to function. minimize the error
(2) In SGD, you have to run through all the samples in your training set for a single update of a parameter in each iteration.
(3) In GD, you either use the entire data or a subset of training data to update a parameter in each iteration.(i) Only (1)
(ii) (1) and (2) only
(iii) (3) and (2) only
(iv) (1), (2) and (3)Q1c. \(c\) In what type of learning labelled training data is used : (i) unsupervised learning (ii) supervised learning (iii) reinforcement learning (iv) active learning20232m
Module 1: Introduction
View this question on its own page →(c) In what type of learning labelled training data is used :
(i) unsupervised learning
(ii) supervised learning
(iii) reinforcement learning
(iv) active learningQ2a. Q.2 (a) What are the important objectives of machine learning?20237m
Module 1: Introduction
View this question on its own page →Q.2 (a) What are the important objectives of machine learning?
Q2a. Give the three computer applications for which machine learning approaches seem appropriate and three for which they seem inappropriate.20227m
Module 1: Introduction
View this question on its own page →Give the three computer applications for which machine learning approaches seem appropriate and three for which they seem inappropriate.
Q2b. Q.2 (b) Explain the inductive biased hypothesis space.20237m
Module 1: Introduction
View this question on its own page →Q.2 (b) Explain the inductive biased hypothesis space.
Q6a. Explain the model of over-fitting and under-fitting. Give the example of over-fitting and under-fitting in two-dimensional data.20227m
Module 1: Introduction
View this question on its own page →Explain the model of over-fitting and under-fitting. Give the example of over-fitting and under-fitting in two-dimensional data.