Data Science Objective Set 1
Which of the following is not considered a cause of confusion about the precise meaning of the data science buzzwords?
The constant evolution of the data science industry and in turn the meaning of the data science buzzwords
Ans:-The speed with which new data science terms are appearing
Which of the following is related to the meaning of the term analytics?
Analytics is about separating a dataset into easy-to-digest chunks and studying them individually and examine how they relate to other parts
Ans:-Analytics is the application of logical and computational reasoning to the component parts obtained in an analysis
Which of the terms relates to the field of business analytics only?
Creating dashboards
Reporting with visuals
Ans:- Qualitative analytics
Which of the following is not considered a data analytics activity?
Ans:-Business case studies
Preliminary data reporting
Optimization of drilling operations
Which of the following is considered data science?
Business case studies
Qualitative analytics
Digital signal processing
Sales forecasting
Given that all activities can be done with ML and all can be done without ML, choose the best answer. Which of the following is considered Data science but not Machine learning?
Creating real-time dashboards
Ans:-Sales forecasting
Fraud prevention
Which of the following is not an example of where Machine Learning is being applied today?
Ans:-Symbolic reasoning
Client retention
Image recognition
From a data scientist’s perspective, the solution of every task begins:
by suggesting a few hypothetical and theoretical solutions to your boss
by gathering your team and deciding on what approach to follow to solve the task
Ans:-with a proper dataset
According to our infographic, which of the following is not considered data science?
Ans:-Big data
Business intelligence
Traditional data science methods
Which of the following is related to the pre-processing of a traditional data set?
Class labelling
Data cleansing
Dealing with missing values
Ans:-All of the above
Which of the following do you encounter when working with big data?
Text data
Integer
Digital image data
Ans:-All of the above
The process of representing observations as numbers is called:
Collecting observations
Ans:-Quantification
A measure that has a business meaning attached is called:
an observation
a quantification
Ans:-a metric
A KPI (Key Performance Indicator) can be best defined as:
the accumulation of observations to show some information
Ans:-a metric that is tightly aligned with your business objectives
a quantification that has a business meaning attached
an observation that can potentially be related to the business goals of a company
The job of a business intelligence analyst always involves the creation of:
reports
dashboards
KPIs
Ans:-All of the above
Which of the following columns from our infographic contain activities that are said to belong to the field of ‘predictive analytics’ and do not aim at explaining past behaviour?
Traditional data
Big data
Business intelligence
Ans:-Traditional methods
In business and statistics, which is the general term that refers to using a model for quantifying causal relationships?
Ans:-regression analysis
factor analysis
cluster analysis
time-series analysis
Which technique can be implemented if you want to reduce the dimensionality of a certain statistical problem?
Ans:-factor analysis
cluster analysis
time-series analysis
all of the above
Which technique is associated with plotting values against time, shown always on the horizontal line?
regression analysis
Ans:-time-series analysis
factor analysis
cluster analysis
When the data is divided into a few groups, you should apply:
factor analysis
Ans:-cluster analysis
time-series analysis
Which of the following statements is true?
The core of machine learning is creating an algorithm, which a computer then uses to find a model that fits the data as best as possible
In machine learning, one does not give the machine instructions on how to find a model. Rather, one provides it with algorithms which give the machine directions on how to learn on its own
A machine learning algorithm is like a trial-and-error process, but the special thing about it, is that each consecutive trial is at least as good as the previous one
Ans:-All of the above
Which line represents the four ingredients of any machine learning algorithm?
Model, data, reward system, objective function
Ans:-Data, model, objective function, optimization algorithm
Model, labelled data, unlabelled data, optimization algorithm
Choose the best answer.
In which type of machine learning is one always working with unlabelled data?
Supervised learning
Ans:-Unsupervised learning
Reinforcement learning
In reinforcement learning, a reward system is being used to improve the machine learning model at hand. The idea of using this reward system is to:
to minimize the error of the model
to minimize the objective function
Ans:-to maximize the objective function
to improve the optimization algorithm