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- 1. Multiple Choice
A _______________is divided into multiple layers and each layer is further divided into several blocks called nodes.
Neural Networks
Convolutional Neural Network (CNN)
Machine learning algorithm
Hidden Layers
- 2. Multiple Choice
The __________________canvas helps you in identifying the key elements related to the problem.
Problem scoping
4Ws Problem
Project cycle
Algorithm
- 3. Multiple Choice
_______is a domain of AI that depicts the capability of a machine to get and analyse visual information and afterwards predict some decisions about it.
NLP
Data Sciences
Augmented Reality
Computer Vision
- 4. Multiple Choice
____________is defined as the percentage of correct predictions out of all the observations.
Predictions
Accuracy
Reality
F1 Score
- 5. Multiple Choice
_________________is the sub-field of AI that is focused on enabling computers to understand and process human languages.
Deep Learning
Machine Learning
NLP
Data Sciences
- 6. Multiple Choice
In___________________, the machine is trained with huge amounts of data which helps it in training itself around the data.
Supervised Learning
Deep Learning
Classification
Unsupervised Learning
- 7. Multiple Choice
NLU Stands for
Neutral Language Understanding
Natural Language Understanding
National Language Understanding
None of the Above
- 8. Multiple Choice
Expand CBT_______________
Computer Behaved Training
Cognitive Behavioural Therapy
Consolidated Batch of trainers
Combined Basic Training
- 9. Multiple Choice
Name any 2 methods of collecting data.
Surveys and Interviews
Rumors and Myths
AI models and applications
Imagination and thoughts
- 10. Multiple Choice
What is the role of modelling in an NLP based AI model?
Modelling in NLP helps in processing of AI model
Modelling is required to make an AI model
In NLP, modelling requires data pre-processing only after which the data is fed to the machine.
Modelling is used in simplification of data acquisition
- 11. Multiple Choice
Recall-Evaluation method is
defined as the fraction of positive cases that are correctly identified.
defined as the percentage of true positive cases versus all the cases where the prediction is true.
defined as the percentage of correct predictions out of all the observations.
comparison between the prediction and reality
- 12. Multiple Choice
Give 2 examples of Supervised Learning models.
Classification and Regression
Clustering and Dimensionality Reduction
Rule Based and Learning Based
Classification and Clustering
- 13. Multiple Choice
Define Machine Learning.
Machine learning refers to computer systems (both machines and software) enables machines to perform tasks for which it is programmed.
Machine Learning refers to projects that allow the machine to work on a particular logic.
Refers to any technique that enables computers to mimic human intelligence.
Machine learning is the study of computer algorithms that improve automatically through experience.
- 14. Multiple Choice
Which of the following is not part of the AI Project Cycle?
Data Exploration
Modelling
Testing
Problem Scoping
- 15. Multiple Choice
________________________ refers to the AI modelling where the machine learns by itself.
Machine Learning
Learning Based
Rule Based
Data Sciences
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