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data science
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1
What is a Scope of Data science ?
Data Cleaning and Preparation
All of the above
Big Data Analytics
Data Collection and Acquisition
2
Which of the following is NOT a type of machine learning?
Computational learning
Unsupervised learning
Reinforcement learning
Supervised learning
3
________ is a technique for evaluating predictive models
k-fold Cross-Validation
Hyper parameter tuning
Decision Trees
Stratified Cross-Validation
4
What technique is commonly used in data science for making predictions?
Machine Learning
Data Storage
Data Encoding
Data cleaning
5
Which type of value does Logistic Regression give ?
all of the above
Between 0 & 1
True or False
Yes or No
6
is the below given formula used for simple linear regression
True
False
7
Which of the following uses data on some object to predict values for another object?
Inferential
Exploratory
None of the mentioned
Predictive
8
How many type of model used in Decision Tree
4
2
6
3
9
Which is the correct type of Logistic Regression
Binomial
Multinomial
All of the above
Ordinal
10
Which techniques formula is this ?
Accuracy
Confusion Matrix
F1-Score
Recall
11
Which of the following is a trait of tidy data?
Each variable in one column
One table for each kind of variable
Each observation in different row
None of the mentioned
12
How many Layer dose Artificial Neural Network consists?
4
2
3
5
13
_____ is the task of dividing the population or data points into number of group
Fuzzy Clustering
Density-Based Clustering
Clustering
Hierarchical Clustering
14
______ is an optimization algorithm which is commonly used to train machine learning models and neural networks
K-NN
Boosting
Decision Trees
Gradient Descent
15
Which of the following is characteristic of Raw Data?
None of the mentioned
Easy to use for data analysis
Data is ready for analysis
Original version of data
16
Which of the following testing is concerned with making decisions using data?
Causal
Hypothesis
None of the mentioned
Probability
17
Which of the following is one of the key data science skills?
Machine Learning
Statistics
All of the mentioned
Data Visualization
18
Which of the following input can be accepted by DataFrame?
All of the mentioned
DataFrame
Structured ndarray
Series
19
Which of the following is performed by Data Scientist?
Create reproducible code
Define the question
Challenge results
All of the mentioned
20
Which of the following is characteristic of Raw Data?
Data is ready for analysis
Original version of data
None of the mentioned
Easy to use for data analysis
21
______ is a statistical method that separates observed variance data into different components
T test
Hypothesis testing
ANOVA
chi-square t test
22
What type of data is considered unstructured?
Data in CSV files
Data in spreadsheets
Text documents and images
Data in relational databases
23
Plots may also be adorned with error bars or tables.
False
True
24
Which of the following function can be used for forecasting?
ets
predict
forecast
all of the mentioned
25
_______ is focuses on the storage and management
warehouse
cloud storage
sql
data base
26
Which of the following is the most important language for Data Science?
Ruby
R
Java
None of the mentioned
27
Which of the following is a common method for data preprocessing?
Data aggregation
Data normalization
Data visualization
Data storage
28
______ data often uses metadata or tags for organization
Unstructured Data
semi-Structured Data
Structured Data
All of the above
29
Which of the following data mining technique is used to uncover patterns in data?
Data merging
Data bagging
Data Dredging
Data booting
30
Which of the following tools is widely used for data visualization in data science?
SQL
Excel
Tableau
All of the mentioned
31
Which of the following is not a step in data analysis?
EDA
None of the mentioned
Clean the data
Obtain the data
32
Support Vector Machines is one of the most popular Supervised Learning algorithms
True
False
33
Andrews curves allow one to plot multivariate data.
False
True
34
______ is the process of deciding which learning technique to use to model our data
Model Analysis
Data Analysis
Model Selection
Data selection
