1. Which of the following are exampes that use Machine Learning
In car Navigation
Credit Card fraud detection
Bank loan application
All of the options (*)
2. Which of the following is the best definition of Artifical Intelligence
Attempt to build machines capable of simulating intelligent human behaviour Attempt to build machines capable of simulating intelligent human behaviour (*)
The science of getting computers to act without being explicitly programmed
Attempt to build machines that look and act like humans
To build computers that are capable of beating all players at chess
3. What does data mean?
Data is information in context
It is the gathering of the figures or facts (*)
It is information that has been processed in a particular format
It is when figures have been processed via machine learning
4. Viewing a summary of all your credit card transactions on a Monday is an example of information?
True (*)
False
5. Information is data in context
True (*)
False
6. Is raw processing power a demonstration of AI?
True
False (*)
7. Rainfall recorded as low, medium, high is an example of
Classification (*)
Regression
8. Regression of data is when
Data can be any numeric value (*)
Data can only be a given discrete value for a list of choices
9. Data shown as a regression can be converted to a classification by grouping it in ranges?
True (*)
False
10. Rainfall recorded as 2,3,0,3,4 is an example of
Classification
Regression (*)
Both Classification and Regression
None of the other options
11. In a loan example "has job is"
(Choose all correct answers)
A label (*)
Dependent data
12. The CRISP model is iterative.
True (*)
False
13. Data Understanding is the first stage of the CRISP model.
True
False (*)
14. Using a methodology such as CRISP decreases the likelihood of random and false discoveries when analyzing data.
True (*)
False
15. As personal computers and devices become more powerful, then the cloud will become irrelevant.
True
False (*)
1. In the CRIP model we cannot move back to a previous stage.
True
False (*)
2. Which one of the following is a model for looking at data via Machine Learning?
CRISP-DM (*)
DM-CRISP
Waterfall Model
Spiral Model
3. Data Understanding is the first stage of the CRISP model.
True
False (*)
4. A 1985 Cray super computer is more powerful than an Apple iPhone 5.
True
False (*)
5. Supervised Learning is
Is when we know the structure of what we are looking for (*)
Is when we do not know the structure of what we are looking for
Is when we can put information in context
Is when we can put data in context
6. Data shown as a regression can be converted to a classification by grouping it in ranges?
True (*)
False
7. Rainfall recorded as 2,3,0,3,4 is an example of
Classification
Regression (*)
Both Classification and Regression
None of the other options
8. Training a program to find faces in a picture is an example of supervised learning
True (*)
False
9. You train your algorithm with test data then test it with training data
True
False (*)
10. Automatic recording of GPS on your phone is an example of data exhaust?
True (*)
False
11. Which of the following is not an example of Machine Learning
Internet Search
Stock trading predictions
Temperature gauge in a car (*)
All of the options
12. The Turing test is
A test on how fast a computer can think.
A test to see whether a computer can imitate a human (*)
A test to see whether a human can imitate a computer
A test to see if a human understands AI.
13. Information can be as simple as presenting data in a different format?
True (*)
False
14. Average results for a class in a quiz is an example of data?
True
False (*)
15. Information is data in context
True (*)
False
2. The single most important thing to know is what should be achieved by using Machine Learning.
True (*)
False
3. We can move onto the next stage of our model without fully knowing the business question we wish to answer.
True
False (*)
4. Can machine learning only be used against one type of task
True
False (*)
5. Which of the following uses machine learning?
Google Searches
Facebook Adds
Netflix Suggestions
All of the options (*)
7. Cloud computing is one of the reasons behind the growth in Machine Learning.
True (*)
False
12. You watch a baseball game without every having seen or read about it and you wish to classify the players based on certain criteria - team, pitcher, fielder etc. This is an example of unsupervised learning.
True (*)
False
13. Having no knowledge of a system that you wish to classify is an example of
Supervised Learning
Unsupervised Learning (*)
Classification
Regression
14. In a loan example "has job is"
(Choose all correct answers)
A label (*)
Dependent data
15. Classification of data is when
Data can be any numeric value
Data can only be a given discrete value for a list of choices (*)
Data can only be categorised with a small subtype of values
Data must be in a small range of values
5. The date and time of a credit card transaction is an example of information?
True
False (*)
7. Viewing the number of visitors to a website from the USA is an example of data
True
False (*)
11. Independent data relys on dependant data.
True
False (*)
14. Supervised Learning is
Is when we know the structure of what we are looking for (*)
Is when we do not know the structure of what we are looking for
Is when we can put information in context
Is when we can put data in context
2. Data normally stored in a table in a spreadsheet is
Structured data (*)
Unstructured Data
Indepedent data
Dependent data
5. Data that can be shown in table format can be described as structured
True (*)
False
7. What is data exhaust?
Is the temporary data that you do not delete on your mobile phone
Is delete data that you are still able to recover
A trail of data that you leave behind you (*)
Is data that you upload to the cloud
8. Machine Learning is
Attempt to build machines capable of simulating intelligent human behaviour Attempt to build machines capable of simulating intelligent human behaviour
The science of getting computers to act without being explicitly programmed (*)
Attempt to build machines that look and act like humans
To build computers that are capable of beating all players at chess
11. Requiring to check if someone has a good credit rating is an exampe of which stage?
Business understanding (*)
Data understanding
Data preparation
Modelling
3. Paper based invoices that come into your office from different sources are examples of
Structured data
Unstructured Data (*)
Indepedent data
Dependent data
15. Recording the tempearture every hour is an example of data
True (*)
False
1. In a binary tree what is the maximum number of children a node can have?
0
1
2 (*)
Any
2. If a node has both its siblings set to null this is called a:
Parent
Leaf (*)
Root
Branch
3. Non binary tree classes still have a left and right node property.
True
False (*)
4. The difference between a tree and a binary tree structure is:
A binary tree is restricted to a maximum of 2 siblings (*)
A binary tree is based around the notion of a root node
A non binary tree cannot be traversed
A non binary tree does not have leaf nodes
5. Information Entropy quantifies how much information there is in an event.
True (*)
False
6. If you know the outcome of an event 100% of the time how much entropy is contained within it?
0 (*)
0.25
0.5
1
7. In a decision tree, it doesn't matter which questions you start with.
True
False (*)
8. In the following tree what would be the result of a Post-Order Traversal?
123456
4275631 (*)
4217536
1243576
9. Which of the following is not a typical example of tree traversal?
Pre Order Traverasal
Post Order Traversal
In Order Traversal
Reverse Order Traversal (*)
10. In the following tree, what would be the result of a Pre-Order Traversal?
123456
4275631
4217536
1243576 (*)
11. Decision trees can only be created using ID3.
True
False (*)
12. Decision trees work better if they have more access to more data.
True (*)
False
13.
This is an example of a recursive method
int power(int a, int n)
{
int result = 1;
for(int i=0;i result *= a;
}
return result;
}
True
False (*)
14. If you create no base case in a recursive method then you will create:
A quicker method
A more efficient method
An infinite loop (*)
An iterative method
15. In recursion, a base case must be defined.
True (*)
False
2. The code below is an example of
void someorder(Node node)
{
if (node == null)
return;
System.out.print(node.data + " ");
printPreorder(node.left);
printPreorder(node.right);
}
Pre Order Traverasal (*)
Post Order Traversal
In Order Traversal
Reverse Order Traversal
4. C4.5 is the successor to ID3.
True (*)
False
5. ID3 is short for:
Interactive Dichotomiser 3
Intersectional Dichotomiser 3
Iterative Dichotomiser 3 (*)
Institutational Dichotomiser 3
7. Which would be the best structure to show a family tree diagram?
Binary Tree
Non Binary Tree (*)
9. Trees are very useful for representing hierarchical structures.
True (*)
False
12. Variance is:
How average of all data items
How far data is spread out (*)
The difference between the largest and smallest item
Measures the relationship between all items
13. Which method uses more memory before iterative and recursive?
Recursive (*)
Iterative
Spiral
No difference
15. Recurive methods can always be written as iterative methods.
True (*)
False
5. Tree traversal is:
The process of searching for only one node
When you wish to remove all leaf nodes in a binary tree
When you set the root node on a binary tree
The process of visting each node once in a abinary tree (*)
9. The first node on a tree is known as a:
Point
Crown
Top
Root (*)
14. Decision trees can only be represented using binary trees.
True
False (*)
6. A method making a call to itself is called:
Iteration
Conditional
Recursion (*)
Search
1. In the following tree what would be the result of a In-Order Traversal?
123456
4275631
4217536 (*)
1243576
8. Binary Trees are made up of a structure known as a:
Point
Intersect
Node (*)
Nodule
13. C4.5 is the successor to ID3.
True (*)
False
1. In a Node class the name of the links to the children are normally called:
Child1, Child2
Left, Right (*)
Sibling1, Sibling2
Top, Bottom
5. Which of the following has the greatest variance?
0,0,0,0
1,2,3,4
1,1,2,2,3,3
1,50,100,2000 (*)
3. Recoding the number of visitors to a website by country is an example of data
True (*)
False
26. Business Understanding is when we understand which question that we want to try and answer.
True (*)
False
27. Cloud computing is one of the reasons behind the growth in Machine Learning.
True (*)
False
28. The reason for the increase use in AI is:
Data is recorded in far greater quantity
Computer processing power has increased
Machine Learning algorithms have improved
All of the above (*)
36. Must every node in a tree have a parent?
True
False (*)
19. Data exhaust allows systems to monitor your behaviours
True (*)
False
38. A binary tree can only store primitive values.
True
False (*)
40. What do we call a node that has 0 children?
Sibling
Leaf (*)
Root
Branch
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