Machine Learning MCQ - Machine learning is the Science of Getting computers to learn without being explicitly programmed. Machine learning works on a simple concept that is understanding with experiences.
Machine Learning Important MCQ
2. The -------- model is then used to predict the changes in the patient’s condition when she takes a certain drug. a. Regression b. Classification c. Generative d. Paradigm
3. As the model is built and trained, it will be able to determine the ------- that a certain
drug will be
most effective for a patient.
a. Matrix b. Mode c. Probability d. Median
4. Applying machine learning algorithms to this ------- IT operations data allows
organizations to proactively respond to potential IT issues.
a. complex b. Simple c. Nontrivial d. Special
5. A ------- model can identify an anomaly before a fraud event is perpetrated.
a. test b. trained c. Validated d. Unique
6. A combination of linear algorithms, neural networks and deep learning is called-----
-- modelling
a. Object b. Ensemble c. Constraint d. Deep
7. Businesses are looking to machine learning techniques to help them anticipate the –
---- and create competitive differentiation.
a. Past b. Present c. Future d. Perfect
8. ------is the technology that allows machines to understand the structure and meaning
of the spoken and Written languages of humans.
a. NLP b. ML c. CNN d. LLT
9. Powerful ------- removes the processing bottleneck of machine learning, thus
allowing machine learning to be embedded in more applications
a. Syntax b. Semantics c. Hardware d. Clothes
10. By using automation, data ---- are able to quickly focus on just one or two
algorithms rather than manually testing many more.
a. Analysts b. Scientists c Operators d. Processors
11. ML is used to reduce --------.
a. Efficiency b. Customer churn c. Accuracy d. Throughput
12. Cross---------provides you with hints when the steps you take (data preparation, data
and feature selection, hyper-parameter fixing, or model selection) are correct.
a. Split b. Validation c. Reference d. Checks
13. Information leaking to test set is called -----
a. Snooping b. Hiding c. Carrying d. Dropping
14. When solving a problem using data and machine learning, you need to analyze the
problem and determine the ideal ------ to optimize.
a. Data b. Metric c. Scale d. Probability
15. ----- is to create a grid search among possible values that your parameters can take
and evaluate the results using the right error or score metric.
a. Hyper-parameter b. Surf c. Browse d. Dip
16. Free lunch refers to interesting results in the -----.
a. Present b. Past c. Future d. Perfect
17. By averaging many different models, you can enhance the signal and rule out the -----
that will often cancel itself .
a. Noise b. Sum c. Error d. Bias
18. The -------competition provides evidence and a detailed illustration about how
heterogeneous models can be stacked together to form more powerful models.
a. Netscape b. Netflix c. Netware d. Drop
19. Automatic --------- creation is possible using polynomial expansion or the support
vector machines class
of machine learning algorithms.
a. Feature b. Data c. Constraint d. Split
20. ------ reduce the influence of redundant variables or even remove them from the
model.
a. Clearing b. Regularization c. Commitment d. Boosting
21. Image files appear as ------ data made up of a series of bits
a. structured b. Unstructured c. Smooth d. Clean
22. The --------function performs the rendering and uses a grayscale color map
a. showimage() b. imshow() c. Show() d. Relu
23. Gaussian filter uses a Gaussian function to define the pixels to -----.
a. rough b. Smooth c. Spikes d. Noise
24. To change the size of image ----- command is used.
a. size b. Invert c. Resize d.rotate
25. Convolutional neural networks filter information across ------ layers, training the
parameters of their Convolutions.
a. Single b. Multiple c. Dual d. Triple
26.------- is an approach to facial recognition based on the overall appearance of a face,
not on its particular details.
a. Decifaces b. .Actofaces c. Eigenfaces d. Hectafaces
27. The fashion MNIST dataset has ----K examples.
a. 60 b. 10 c. 70 d. 75
28.Human ---- is crucial in Neural network implementation.
a. Feature b. Bias c. Effort d. Type
29. ---------data is a type of short text that you represent using binary variables.
a. Class b. Categorical c. Set d. Optimal
30. Storing documents in a document matrix form can be memory intensive. This
problem is solved by-----
a. sparse matrices b. voluminous data c. Trivial data d. Adding zeros
machine learning mcq pdf download
Understanding of machine learning