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ML Quiz
ML Quiz
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1
6) _______ is the machine learning algorithms that can be used with labeled data.
B.Clustering algorithms
A. Regression algorithms
D.All of the above
C.Association algorithms
2
19) Automatic Speech Recognition systems find awide variety of applications in the _________domains.
A. Medical Assistance
D.All of the above
B.Industrial Robotics
C.Defence & Aviation
3
29)machine learning algorithms build a model based on sample data known as
C. Data Training
D. All of the Above
A. Transfer Data
B. Training Data
4
Which machine learning models are trained tomake a series of decisions based on rewards feedback
C.Reinforcement learning
B.Unsupervised learning
A. Supervised learning
D.All of the above
5
16) Which Language is Best for Machine Learning?
A. C
B.Java
C.Python
D.HTML
6
What is machine learning ?
the science of getting computers to act without being explicitly programed
Machine Learning is a Form of AI that Enables a System to Learn from Data.
C.Both A and B
D.None of the above
7
If I am using all features of my dataset and Iachieve 100% accuracy on my training set, but~70% on validation set
B) Nothing, the model is perfect
A) Underfitting
C) Overfitting
NONE
8
49)Which of the following metrics can be used toevaluate a model with a continuous output variable?
B. Accuracy
D. Mean-Squared-Error
C. Logloss
A. Precision-Recall Curve
9
33)The machine learning algorithms that can be used with unlabeled data is ...........
C. Clustering algorithms
D. unsupervised learning
B. Instance-based algorithms
A. Regression algorithms
10
26)Logistic regression...
B. can be used to predict a house price
C. Can be used to find the size of a tumor fromother parameter
A. is used to find a continuous value
D. Is used for classification
11
Support vectors are the data points that lieclosest to the decision surface.
True
False
12
18) The unsupervised learning problems can begrouped as _______.
A. Clustering
D.None of the above
C.Both A and B
B.Association
13
ans based on th image below
80%
90%
75%
70%
14
22) Features of Machine Learning are______.
C.Business intelligence
A. Automation
B.Improved customer experience
D.All of the above
15
17) The supervised learning problems can begrouped as _______.
A. Regression problems
D.None of the above
B.Classification problems
C.Both A and B
16
9) Which among the following algorithms are usedin Machine learning?
C.K-Nearest Neighbors
A. Naive Bayes
D.All of the above
B.Support Vector Machines
17
10) Replace missing values with mean/median/modehelps to handle missing or corrupted data in adataset. True/False?
False
True
18
30)............. is a machine learning technique that helps in detecting the outliers in data.
C. Anamoly Detection
A. Clustering
D. None of the above
B. Classification
19
11) ________ is a disadvantage of decision trees?
C.Both A and B
D.None of the above
A. Decision trees are robust to outliers
B.Decision trees are prone to be overfit
20
SVM stands for?
D. All the Above
B. Support Vector Machine
A. Simple Vector Machine
C. Super Vector Machine
21
8) The Real-world machine learning use cases are_______.
D.All of the above
C.Fraud detection
B.Chatbots
A. Digital assistants
22
31)What is true about Machine Learning?
D. All of the Above
C. ML is a field of AI consisting of learning algorithms
A. Machine Learning (ML) is that field of computerscience
B. ML is a type of artificial intelligence
23
Machine learning approaches can be traditionallycategorized into ______ categories.
3
9
7
4
24
Machine Learning can automate tasks,especially the ones that only humans can performwith their innate intelligence.
False
True
25
20) The term machine learning was coined by__________.
C.Guido van RossumC.Guido van Rossum
A. James Gosling
D.None of the above
B.Arthur Samuel
26
32)The supervised learning problem can be groupedas
B. Classification problems
A. Regression problems
D. None of the above
C. Both A & B
27
15) _______ is the scenario when the model fails todecipher the underlying trend in the input data.
D.None of the above
B.Underfitting
A. Overfitting
C.Both A and B
28
3) Application of Machine learning is __________.
A. email filtering
C.face recognition
B.sentimental analysis
D.All of the above
29
The categories in which Machine learning approaches can be traditionally categorized are___ .
B.Unsupervised learning
A. Supervised learning
B.Unsupervised learning
D.All of the above
30
52)Which statement is true about outliers in Linearregression?
C. Can’t say
A. Linear regression model is not sensitive to outliers
D) None of these
B. Linear regression model is sensitive to outliers
31
14) ________ is used as an input to the machinelearning model for training and prediction purposes.
B.Feature Vector
A. Feature
D.None of the above
C.Both A and B
32
12) ________ is a part of machine learning thatworks with neural networks.
B.Deep learning
D.None of the above
A. Artificial inteligence
C.Both A and B
33
27)Which of these are associated with SVM?
C. hyperplanes
D. all
B. non-linear
A. linear
34
25)The faceapp has simulated a persons face based on targetted age. This is example of
C. prediction
NONE
D. great artwork
B. logistic regression classifier
35
best fit line method for data in LinearRegression?
Both A and B
Least Square Error
Maximum Likelihood
Logarithmic Loss
36
Which statement is true about outliers in Linear regression?
Linear regression model is sensitive to outliers
Linear regression model is not sensitive to outliers
Can’t say
D) None of these
37
24)All data is labeled and the algorithms learn topredict the output from the input data
C. supervised learning
D. unsupervised learning
A. Dataset
B. Classifiers
38
The effectiveness of an SVM depends upon:
B) Kernel Parameters
A) Selection of Kernel
D) All of the above
C) Soft Margin Parameter C
39
Machine learning is an application of
D.None of the above
A. Blockchain
C.Both A and B
B.Artificial Intelligence
40
28)how do you handle missing or corrupted data in a dataset?
A. Drop missing rows or columns
C. Replace missing values with mean/median/mode
D. All of the Above
B. Assign a unique category to missing values
41
What will happen with bias and variance as youincrease the size of training data in linearregression?
C. Bias increases and Variance decreases
A. Bias increases and Variance increases
B. Bias decreases and Variance increases
D. Can’t Say
42
Linear separator, Hyper plane
C. f{x)=sign(w.x+b)
A. f(x)=sign(w/x+b)
f(x)=sign(w-x+b)
B. f(x)=sign(w+x+b)
