Solution

Both A) and B) are false because nothing specific is implied from the statement.

Solution

The articles a/an is used in front of indefinite noun

The article the is used in front of a definite noun.

Solution

Pun - A pun is a figure of speech that contains a “play” on words, such as using words that mean one thing to mean something else or words that sound alike in as a means of changing meaning.

A sleeping bull is called a bull-dozer.

Baseball players eat on home plates.

Simile - Simile is a figure of speech in which two dissimilar things are compared to each other using the terms “like” or “as.”

She’s as pretty as a picture.

I’m pleased as punch

Hyperbole - Hyperbole is a figure of speech that utilizes extreme exaggeration to emphasize a certain quality or feature.

I have a million things to do.

This suitcase weighs a ton.

Paradox - A paradox is a statement that may seem contradictory but can be true (or at least make sense).Here are some thought-provoking paradox examples: Save money by spending it. If I know one thing, it's that I know nothing. This is the beginning of the end.

Solution

When we feel like giving up, if we have something smaller or more achievable to encourage us to go on, then we are more likely to continue our mission. In the passage it is given ‘However, as soon as I remember the intent I have for living, I come back to life, I am excited’

Solution

Shapes are similar to one another if they are proportional to one another. Scale factors are used to increase all side lengths by the same amount.

Solution

There are four types of Transformations.

• Translation
• Reflection
• Rotation
• Enlargement

Solution

ABC has been rotated by 90anti-clockwise through (0,0).

Solution

Transformations, such as translation, enlargement, reflection and rotation, are all ways of changing the size (or) position.

Solution

• The size and orientation remains the same.
• Rotation spins a shape and changes orientation (not happened).
• The shape has been moved (Translated).

Solution

Solution

Option 3.

Solution

Option 3.

Solution

Option 4.

Solution

The heuristic function in heuristic search algorithms, such as A* search, estimates the cost to reach the goal from the current node. It does not estimate the cost from the start to the current node, nor the overall path cost through the node; those are estimated by other functions within such algorithms (like g(n) for the cost from the start).

Solution

Solution

The increasing number of hidden layers may results in the time taken for minimizing the error as low

Solution

Principal component analysis is a technique for feature extraction.

so it combines our input variables in a specific way, we can drop the "least important" variables while still retaining the most valuable parts of all of them!

When we apply PCA, it is obvious that the independent variables in our observations become less interpretable.

PCA is a kind of unsupervised learning, meaning no independent variable in this analysis

Solution

The expression ( ∀x (P(x) -> Q(x)) ) means that for every x, if x is a student, then x studies.

Solution

The negation translates to "It is not the case that everyone is prepared," which equates to "At least one person is not prepared."

Solution

Likelihood weighting involves collecting samples from a prior, then weighting them by their likelihood to compute expectations concerning an upcoming value.

Solution

The primary procedure in variable elimination is summing out variables to compute marginal probabilities of the remaining variables.

Solution

In Gibbs sampling, each variable is sampled from its conditional distribution given the values of all other variables. For 4 variables, each must be updated once per iteration, resulting in 4 updates.

Solution

In an HMM with 3 states, the transition probability matrix is a 3×3 matrix, where each element defines the probability of transitioning from one state to another, requiring 9 parameters in total.

Solution

In decision trees among all the possible splits, it chooses the one that maximizes the gain not the one that minimizes it. Or it chooses not to split the leaf at all. All other three are the correct statements about the Decision tree.

Solution

Manhattan distance, d = |x1 – x2| + |y1 – y2|

= |9 – 3| + |7 – 4|

= |6| + |3|

= 9

Solution

Information Gain, IG = Ebefore – Esplit

= 1 – 0.67

= 0.33

Solution

P(W/A) = 3/5 and P(W/B) = 5/9

According to Bayes Theorem we know that,

P(B/W) = 𝑃(𝑊/𝐵)∗𝑃(𝐵) / 𝑃(𝑊/𝐵)∗𝑃(𝐵)+𝑃(𝑊/𝐴)∗𝑃(𝐴)

P(B/W) = 5/9∗1/2 / (5/9∗1/2)+(3/5∗1/2)

P(B/W) = 5/18 / 104/180

P(B/W) = 50/104

Solution

The bias-variance trade-off suggests finding a balance between underfitting and overfitting.

Solution

Backpropagation is an algorithm commonly used to train the neural networks so that they can perform the tasks more accurately. The idea behind is to test how wrong the neural network is and then to correct it.

Solution

As per the definition, ‘P’ is some performance measure that needs to be improved over time. So, accuracy is one of the ways we can measure the performance of predicting future prices.

As per the definition, ‘T’ is the task, so The price prediction task would actually be a ‘T’ in our case.

And, the process of learning to find the patterns within newer data with past data refers to experience ‘E’

Solution

D, A, B, E, C, F, G.

Solution

PCA tends to find linear correlation between the given variables using eigenvectors and eigenvalues. Hence, they give maximum information when data has linear spread and vice-versa.

Hence, when data has a circular spread the performance is not very good.

Solution

Decision Trees algorithm will always try to maximize Information Gain.