MFDM™ AI – The Renaissance Introduction and Multiple choice Questions and Answers

MFDM™ AI – The Renaissance Interview Question-Answer

Q.1 Non-biological entities exhibiting complex, goal-oriented behavior is called __________.

A. Artificial Intelligence

       B. Machine Learning

       C. Deep Learning

       D. All the options

Ans : Artificial Intelligence

Q.2 Which of the following is/are AI based product(s)?

       A. Siri

       B. Alexa

       C. Google AI Eye Doctor

       D. Google Virtual Assistant

       E. All the options

Ans : All the options

Q.3 Why is Artificial Intelligence (AI) gaining importance?

       A. Avanlanche of Data Generation

       B. Need for more Computational Power

       C. Need for better Algorithms

       D. All the options

Ans : All the options

Q.4 Training data is used in model evaluation.

       A. True

       B. False

Ans : False

Q.5 Which among the following is better for processing Spatial Data?

       A. GPU

       B. FPGA

       C. CPU

       D. None of the mentioned

Ans : FPGA

Q.6 The ML model stage which aids in uncovering the hiddens patterns of data.

       A. Model Evaluation

       B. Data Gathering

       C. Exploratory Data Analysis

       D. Data Cleaning

Ans : Data Cleaning

Q.7 ____________ learning aids in uncovering hidden patterns from unlabeled data.

       A. Unsupervised

       B. Supervised

       C. Reinforcement

Ans : Unsupervised

Q.8 ML data can be represented in ‘_____________’ form(s).

       A. Scalar and Vector

       B. Matrix and Spatial

       C. All the above options

Ans : Scalar and Vector

Q.9 The MFDM™ Execution Model has __________ stages.

       A. 5 stages

       B. 3 stages

       C. 4 stages

Ans : 3 stages

Q.10 In Linear Regression, plotting the relationship between dependent and independent variables will form a __________.

       A. Parabola

       B. Sigmoid Curve

       C. Straight Line

       D. All the options

Ans : All the options

Q.11 Naive Bayes works based on the idea that Predictor variables in the ML process is __________ of each other.

       A. Independent

       B. Dependent

Ans : Dependent

Q.12 Scenario: Number of calories burnt is calculated based on the hours of exercise. Which is the Response variable in this scenario?

       A. Hours of exercise

       B. Number of calories burnt

       C. None of the mentioned

Ans : Number of calories burnt

Q.13 __________ is the process of splitting whole data into smaller chunks in NLP.

       A. Tokenisation

       B. Lemmatization

       C. Stemming

Ans : Tokenisation

Q.14 In Supervised Learning Algorithm Linear Regression, the dependent Response variable is __________.

       A. Discrete only

 B. Continuous or Discrete

       C. Continuous only

Ans : Continuous only

Q.15 The MFDM™ Execution Model life cycle has __________ phases.

       A. Three

       B. Four

       C. Five

Ans : Three

Q.16 Benefits of MFDM™ include:

       A. Customized services for Stakeholders

       B. Enables human resources to execute more complex and better quality work

       C. Drives Superior Customer Experience

       D. All the options

Ans : All the options

Q.17 “Scenario: You are given some news articles to group into sets that have the same story.
Which type of learning would you suggest to address this issue?”

       A. Unsupervised

       B. Reinforcement

       C. Supervised

Ans : Unsupervised

Q.18 In an ML model, the response variable can be __________.

       A. Continuous only

 B. Continuous or Discrete

       C. Discrete only

Ans : Continuous or Discrete

Q.19 Which among the following is not an application of Natural Language Programming (NLP)?

       A. ChatBot

       B. Sentimental Analysis

       C. Speech Recognition

       D. Market Basket Analysis

Ans : Speech Recognition

Q.20 The key feature(s) of Ignio™ include(s) __________

       A. Pro-active

       B. Reliable

       C. Agile

       D. All the options

Ans : All the options

Q.21 A Python package used in text analysis and natural language processing.

       A. Pandas

       B. Scikit-learn

       C. NLTK

Ans : NLTK

Q.22 Classification problems aid in predicting __________ outputs.

       A. Continuous only

       B. Categorical or Discrete only

       C. All the options

Ans : Categorical or Discrete only

Q.23 Key characteristic(s) of MFDM™ include(s):

       A. Ubiquitous

       B. Polymorphic

       C. Business First

       D. Inherently Secure

       E. All the options

Ans : All the options

Q.24 Machine Learning is a subset of __________.

       A. Deep Learning

       B. Artificial Intelligence

       C. None of the mentioned

Ans : Artificial Intelligence

Q.25 In Reinforcement Learning, algorithms that learn from trial and error are called __________.

       A. Environments

       B. Policies

       C. Agents

       D. Rewards

Ans : Agents

Q.26 A part of Machine Learning where an agent learns to behave optimally, by performing actions that will either be rewarded or punished.

       A. Unsupervised Learning

       B. Supervised Learning

       C. Reinforcement Learning

Ans : Reinforcement Learning

Q.27 A Machine Learning technique that helps in detecting the outliers in data.

       A. Regression

       B. Anamoly Detection

       C. Classification

       D. Clustering

Ans : Classification

Q.28 The MFDM™ Framework constitutes __________.

       A. Collaboration Platform

       B. Enterprise Intelligence Platform

       C. Enterprise Response Engine

       D. All the options

Ans : All the options

Q.29 GPUs enable perfect processing of __________ data.

       A. Vector

       B. Scalar

       C. Spatial

Ans : Vector

Q.30 Lemmatization helps in morphological analysis of words.

       A. True

       B. False

Ans : True

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Q.31 SEMMA is a patented model.

       A. True

       B. False

Ans : True

Q.32 In a Decision Tree, the leaf node represents a __________.

       A. Response variable

       B. Predictor variable

Ans : Response variable

Q.33 CRISP-DM is an open standard process model that contains _ stages.

       A. 5

       B. 4

       C. 6

       D. 7

Ans : 6

Q.34 Logistic Regression is a type of __________ problem.

       A. Classification

       B. Regression

       C. Clustering

Ans : Classification

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Q.35 AI made its emergence with _ evolutionary stages.

       A. 5

       B. 4

       C. 3

       D. 1

Ans : 3

Q.36 In the three evolutionary stages of artificial intelligence (AI), ‘________’ intelligence refers to applying AI only to specific tasks.

       A. General

       B. Narrow

       C. Super

Ans : Narrow

Q.37 In a Decision Tree Algorithm, __________ measure is used to measure the uncertainity present in data.

       A. Entropy

       B.Information Gain

       C. None of the mentioned

Ans : Entropy

Q.38 The __________ stage of the CRISP-DM process focuses on understanding the objectives and requirements of a project.

       A. Business Understanding

       B. Modeling

       C. Data Preparation

       D. Deployment

       E. Evaluation

       F. Data Understanding

Ans : Business Understanding

Q.39 _____________ refers to the intelligence capability of computers to surpass that of humans.

       A. General Intelligence

       B. Narrow Intelligence

       C. Super Intelligence

Ans : Super Intelligence

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Q.40 Scenario: Number of calories burnt is calculated based on the hours of exercise. Which is the Predictor variable in this scenario?

       A. Hours of exercise

       B. None of the mentioned

       C. Number of calories burnt

Ans : Number of calories burnt


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