#Python_Quiz.
Check Out The Code Properly.
Check Out The Code Properly.
class Count:
def __init__(self, count=0):
self.__count=count
a=Count(2)
b=Count(2)
print(id(a)==id(b), end = " " )
c= "hello"
d= "hello"
print(id(c)==id(d))Date: 24th Sept, 2022
Company name: Musigma
Role: Data Analyst
Topic: Powerbi, Tableau, Excel
1. What is x-velocity in Power Pivot?
X-Velocity is the in-memory analytics engine behind Power Pivot that loads and handles huge data in Power BI. It stores data in columnar storage that results in faster processing.
2. What is Gantt chart in Tableau ?
A Tableau Gantt chart illustrates the duration of events as well as the progression of value across the period. Along with the time axis, it has bars. The Gantt chart is primarily used as a project management tool, with each bar representing a project job.
3. What in Excel is a macro?
An Excel macro is an algorithm or a group of steps that helps automate an operation by capturing and replaying the steps needed to finish it. Once the steps have been saved, you may construct a Macro that the user can alter and replay as often as they like.
4. Power BI can connect to which data sources?
The data source is the point from which the data has been retrieved. It can be anything like files in various formats (.xlsx, .csv, .pbix, .xml, .txt etc), databases (SQL database, SQL Data Warehouse, Spark on Azure HDInsight), or form content packets like Google Analytics or Twilio.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: Musigma
Role: Data Analyst
Topic: Powerbi, Tableau, Excel
1. What is x-velocity in Power Pivot?
X-Velocity is the in-memory analytics engine behind Power Pivot that loads and handles huge data in Power BI. It stores data in columnar storage that results in faster processing.
2. What is Gantt chart in Tableau ?
A Tableau Gantt chart illustrates the duration of events as well as the progression of value across the period. Along with the time axis, it has bars. The Gantt chart is primarily used as a project management tool, with each bar representing a project job.
3. What in Excel is a macro?
An Excel macro is an algorithm or a group of steps that helps automate an operation by capturing and replaying the steps needed to finish it. Once the steps have been saved, you may construct a Macro that the user can alter and replay as often as they like.
4. Power BI can connect to which data sources?
The data source is the point from which the data has been retrieved. It can be anything like files in various formats (.xlsx, .csv, .pbix, .xml, .txt etc), databases (SQL database, SQL Data Warehouse, Spark on Azure HDInsight), or form content packets like Google Analytics or Twilio.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Check out our latest YouTube video on ROC-AUC Curve Now. Link given below
👉🏻https://youtu.be/fnTgDDlc4eY
👉🏻https://youtu.be/fnTgDDlc4eY
Date: 25th Sept, 2022
Company Name: VMware
Role: Data scientist
Topic: Perceptron, ARM, Activation Function
1. What is Perceptron? And how does it Work?
If we focus on the structure of a biological neuron, it has dendrites which are used to receive inputs. These inputs are summed in the cell body and using the Axon it is passed on to the next biological neuron. Similarly, a perceptron receives multiple inputs, applies various transformations and functions and provides an output. A Perceptron is a linear model used for binary classification. It models a neuron which has a set of inputs, each of which is given a specific weight. The neuron computes some function on these weighted inputs and gives the output.
2. What are the activation functions?
Activation function translates the inputs into outputs. Activation function decides whether a neuron should be activated or not by calculating the weighted sum and further adding bias with it. The purpose of the activation function is to introduce non-linearity into the output of a neuron.
There can be many Activation functions like:
Linear or Identity
Unit or Binary Step
Sigmoid or Logistic
Tanh
ReLU
Softmax.
3) 1.What do you mean by Associative Rule Mining (ARM)?
Associative Rule Mining is one of the techniques to discover patterns in data like features (dimensions) which occur together and features (dimensions) which are correlated. It is mostly used in Market-based Analysis to find how frequently an itemset occurs in a transaction. Association rules have to satisfy minimum support and minimum confidence at the very same time. Association rule generation generally comprised of two different steps:
“A min support threshold is given to obtain all frequent item-sets in a database.”
“A min confidence constraint is given to these frequent item-sets in order to form the association rules.”
Support is a measure of how often the “item set” appears in the data set and Confidence is a measure of how often a particular rule has been found to be true.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company Name: VMware
Role: Data scientist
Topic: Perceptron, ARM, Activation Function
1. What is Perceptron? And how does it Work?
If we focus on the structure of a biological neuron, it has dendrites which are used to receive inputs. These inputs are summed in the cell body and using the Axon it is passed on to the next biological neuron. Similarly, a perceptron receives multiple inputs, applies various transformations and functions and provides an output. A Perceptron is a linear model used for binary classification. It models a neuron which has a set of inputs, each of which is given a specific weight. The neuron computes some function on these weighted inputs and gives the output.
2. What are the activation functions?
Activation function translates the inputs into outputs. Activation function decides whether a neuron should be activated or not by calculating the weighted sum and further adding bias with it. The purpose of the activation function is to introduce non-linearity into the output of a neuron.
There can be many Activation functions like:
Linear or Identity
Unit or Binary Step
Sigmoid or Logistic
Tanh
ReLU
Softmax.
3) 1.What do you mean by Associative Rule Mining (ARM)?
Associative Rule Mining is one of the techniques to discover patterns in data like features (dimensions) which occur together and features (dimensions) which are correlated. It is mostly used in Market-based Analysis to find how frequently an itemset occurs in a transaction. Association rules have to satisfy minimum support and minimum confidence at the very same time. Association rule generation generally comprised of two different steps:
“A min support threshold is given to obtain all frequent item-sets in a database.”
“A min confidence constraint is given to these frequent item-sets in order to form the association rules.”
Support is a measure of how often the “item set” appears in the data set and Confidence is a measure of how often a particular rule has been found to be true.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
#PYTHON_QUIZ
CHECK THIS CODE BELOW:
CHECK THIS CODE BELOW:
try:
list = 5*[0]+5*[10]
x = list[9]
print("CloudyML")
except IndexError:
print("Pandas are Pythons")
else:
print("Data Science is")
finally:
print("Love of my life")Date: 08th Sept, 2022
Company Name: Fractal Analytics
Role: Data Analyst
Topic: SQL, python, PowerBI
1. What is SQL Injection?
SQL injection is a sort of flaw in website and web app code that allows attackers to take control of back-end processes and access, retrieve, and delete sensitive data stored in databases. In this approach, malicious SQL statements are entered into a database entry field, and the database becomes exposed to an attacker once they are executed. By utilising data-driven apps, this strategy is widely utilised to get access to sensitive data and execute administrative tasks on databases.
Q2. What are sets and groups in Tableau?
Sets and groups are used group data based on some specific conditions. The main difference between these two is that a group can divide the dataset into multiple groups whereas a set can have only two options which is either in or out. A user should choose to apply group or sets based on the requirements.
Q3. What is Power Pivot & Power Query?
Power Pivot is an add-on provided by Microsoft for Excel since 2010. Power Pivot was designed to extend the analytical capabilities and services of Microsoft Excel.
Power Query is a business intelligence tool designed by Microsoft for Excel. Power Query allows you to import data from various data sources and will enable you to clean, transform and reshape your data as per the requirements. Power Query allows you to write your query once and then run it with a simple refresh.
Q4. State some ways to improve the performance of Tableau?
Use an Extract to make workbooks run faster
Reduce the scope of data to decrease the volume of data
Reduce the number of marks on the view to avoid information overload
Try to use integers or Booleans in calculations as they are much faster than strings
Hide unused fields
Use Context filters
Reduce filter usage and use some alternative way to achieve the same result
Use indexing in tables and use the same fields for filtering
Remove unnecessary calculations and sheets.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company Name: Fractal Analytics
Role: Data Analyst
Topic: SQL, python, PowerBI
1. What is SQL Injection?
SQL injection is a sort of flaw in website and web app code that allows attackers to take control of back-end processes and access, retrieve, and delete sensitive data stored in databases. In this approach, malicious SQL statements are entered into a database entry field, and the database becomes exposed to an attacker once they are executed. By utilising data-driven apps, this strategy is widely utilised to get access to sensitive data and execute administrative tasks on databases.
Q2. What are sets and groups in Tableau?
Sets and groups are used group data based on some specific conditions. The main difference between these two is that a group can divide the dataset into multiple groups whereas a set can have only two options which is either in or out. A user should choose to apply group or sets based on the requirements.
Q3. What is Power Pivot & Power Query?
Power Pivot is an add-on provided by Microsoft for Excel since 2010. Power Pivot was designed to extend the analytical capabilities and services of Microsoft Excel.
Power Query is a business intelligence tool designed by Microsoft for Excel. Power Query allows you to import data from various data sources and will enable you to clean, transform and reshape your data as per the requirements. Power Query allows you to write your query once and then run it with a simple refresh.
Q4. State some ways to improve the performance of Tableau?
Use an Extract to make workbooks run faster
Reduce the scope of data to decrease the volume of data
Reduce the number of marks on the view to avoid information overload
Try to use integers or Booleans in calculations as they are much faster than strings
Hide unused fields
Use Context filters
Reduce filter usage and use some alternative way to achieve the same result
Use indexing in tables and use the same fields for filtering
Remove unnecessary calculations and sheets.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Date: 27-09-2022
Company name: TCS
Role: ML Engineer
Topic: SVM, bias, correlation and covariance
1. What are Support Vectors in SVM?
A Support Vector Machine (SVM) is an algorithm that tries to fit a line (or plane or hyperplane) between the different classes that maximizes the distance from the line to the points of the classes.
In this way, it tries to find a robust separation between the classes. The Support Vectors are the points of the edge of the dividing hyperplane.
2. What is Bias in Machine Learning?
Bias in data tells us there is inconsistency in data. The inconsistency may occur for several reasons which are not mutually exclusive.
For example, a tech giant like Amazon to speed the hiring process they build one engine where they are going to give 100 resumes, it will spit out the top five, and hire those.
When the company realized the software was not producing gender-neutral results it was tweaked to remove this bias.
3. Explain Correlation and Covariance?
Covariance signifies the direction of the linear relationship between two variables, whereas correlation indicates both the direction and strength of the linear relationship between variables.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: TCS
Role: ML Engineer
Topic: SVM, bias, correlation and covariance
1. What are Support Vectors in SVM?
A Support Vector Machine (SVM) is an algorithm that tries to fit a line (or plane or hyperplane) between the different classes that maximizes the distance from the line to the points of the classes.
In this way, it tries to find a robust separation between the classes. The Support Vectors are the points of the edge of the dividing hyperplane.
2. What is Bias in Machine Learning?
Bias in data tells us there is inconsistency in data. The inconsistency may occur for several reasons which are not mutually exclusive.
For example, a tech giant like Amazon to speed the hiring process they build one engine where they are going to give 100 resumes, it will spit out the top five, and hire those.
When the company realized the software was not producing gender-neutral results it was tweaked to remove this bias.
3. Explain Correlation and Covariance?
Covariance signifies the direction of the linear relationship between two variables, whereas correlation indicates both the direction and strength of the linear relationship between variables.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
🚨Job Opening Alert🚨
Role: Data Analyst
Company: Physicswallah
Exp: fresher
Link: https://ai.cloudyml.com/3RgwuDG
Role: Trainee Business Analyst
Company: Hrmantra Software Pvt. Ltd.
Exp: Fresher
Link: https://ai.cloudyml.com/3xUIhAT
Role: Data Scientist
Company : vital
Exp: 6 month experience
Link: https://ai.cloudyml.com/3fo41P2
Role: Data Scientist
Company : smartanalyst
Exp: Fresher
Link : https://ai.cloudyml.com/3DSZ5Mx
All the best💙
Role: Data Analyst
Company: Physicswallah
Exp: fresher
Link: https://ai.cloudyml.com/3RgwuDG
Role: Trainee Business Analyst
Company: Hrmantra Software Pvt. Ltd.
Exp: Fresher
Link: https://ai.cloudyml.com/3xUIhAT
Role: Data Scientist
Company : vital
Exp: 6 month experience
Link: https://ai.cloudyml.com/3fo41P2
Role: Data Scientist
Company : smartanalyst
Exp: Fresher
Link : https://ai.cloudyml.com/3DSZ5Mx
All the best💙
Watch our latest YouTube video to know about 6 important SQL Keywords that will help you to crack interview as fresher.
Check Now - https://youtu.be/_NRPolXRKDY
Check Now - https://youtu.be/_NRPolXRKDY
Date: 28-09-2022
Company name: Swiggy
Role: Data Analyst
Topic: python, SQL, excel, tableau
1. How many report formats are available in Excel?
There are three report formats available in Excel; they are:
1. Compact Form
2. Outline Form
3. Tabular Form
2. What are sets in Tableau?
Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computed sets update as your data changes. Alternatively, a set can be based on specific data point in your view.
3. What is the difference between DROP and TRUNCATE commands?
DROP command removes a table and it cannot be rolled back from the database whereas TRUNCATE command removes all the rows from the table.
4. What is slicing in Python?
Ans: Slicing is used to access parts of sequences like lists, tuples, and strings. The syntax of slicing is-[start:end:step]. The step can be omitted as well. When we write [start:end] this returns all the elements of the sequence from the start (inclusive) till the end-1 element. If the start or end element is negative i, it means the ith element from the end.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: Swiggy
Role: Data Analyst
Topic: python, SQL, excel, tableau
1. How many report formats are available in Excel?
There are three report formats available in Excel; they are:
1. Compact Form
2. Outline Form
3. Tabular Form
2. What are sets in Tableau?
Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computed sets update as your data changes. Alternatively, a set can be based on specific data point in your view.
3. What is the difference between DROP and TRUNCATE commands?
DROP command removes a table and it cannot be rolled back from the database whereas TRUNCATE command removes all the rows from the table.
4. What is slicing in Python?
Ans: Slicing is used to access parts of sequences like lists, tuples, and strings. The syntax of slicing is-[start:end:step]. The step can be omitted as well. When we write [start:end] this returns all the elements of the sequence from the start (inclusive) till the end-1 element. If the start or end element is negative i, it means the ith element from the end.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Our Data Science & Analytics Mega Combo Course is for those who wanna switch to Data Science domain from any background.
➡️ VISIT OUR WEBSITE NOW
Our Unique Course Features are
✅ Hands-on Practical Learning through Assignments and capstone projects.
✅ Personal Chat Support for Doubt Clearance Everyday.
✅ Get One Month of PAID Internship after course completion (Stipend will be 8K)
NO PRIOR CODING EXPERIENCE IS REQUIRED TO JOIN.
➡️ VISIT OUR WEBSITE NOW
🚨NOTE: AFTER COMPLETING THE COURSE, IF YOU DO THE INTERNSHIP (WHICH WILL BE FLEXIBLE WITH TIME) FOR ONE MONTH THEN YOUR COURSE FEE WILL BE REFUNDED AS STIPEND (8K) FOR MEGA COMBO COURSE.
HURRY UP! Check The Course & Enroll Today
➡️ VISIT OUR WEBSITE NOW
Our Unique Course Features are
✅ Hands-on Practical Learning through Assignments and capstone projects.
✅ Personal Chat Support for Doubt Clearance Everyday.
✅ Get One Month of PAID Internship after course completion (Stipend will be 8K)
NO PRIOR CODING EXPERIENCE IS REQUIRED TO JOIN.
➡️ VISIT OUR WEBSITE NOW
🚨NOTE: AFTER COMPLETING THE COURSE, IF YOU DO THE INTERNSHIP (WHICH WILL BE FLEXIBLE WITH TIME) FOR ONE MONTH THEN YOUR COURSE FEE WILL BE REFUNDED AS STIPEND (8K) FOR MEGA COMBO COURSE.
HURRY UP! Check The Course & Enroll Today
Date: 29-09-2022
Company name: Capgemini
Role: Data Scientist
Topic: ACID, KPI, Encoding
1. What is the ACID property in a database?
The full form of ACID is atomicity, consistency, isolation, and durability.
• Atomicity refers that if any aspect of a transaction fails, the whole transaction fails and the database state remains unchanged.
• Consistency means that the data meets all validity guidelines.
• Concurrency management is the primary objective of isolation.
• Durability ensures that once a transaction is committed, it will occur regardless of what happens in between such as a power outage, fire, or some other kind of disturbance.
2. What is the meaning of KPI in statistics?
KPI is an acronym for a key performance indicator. It can be defined as a quantifiable measure to understand whether the goal is being achieved or not. KPI is a reliable metric to measure the performance level of an organization or individual with respect to the objectives. An example of KPI in an organization is the expense ratio.
3. Explain One-hot encoding and Label Encoding. How do they affect the dimensionality of the given dataset?
One-hot encoding is the representation of categorical variables as binary vectors. Label Encoding is converting labels/words into numeric form. Using one-hot encoding increases the dimensionality of the data set. Label encoding doesn’t affect the dimensionality of the data set. One-hot encoding creates a new variable for each level in the variable whereas, in Label encoding, the levels of a variable get encoded as 1 and 0.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: Capgemini
Role: Data Scientist
Topic: ACID, KPI, Encoding
1. What is the ACID property in a database?
The full form of ACID is atomicity, consistency, isolation, and durability.
• Atomicity refers that if any aspect of a transaction fails, the whole transaction fails and the database state remains unchanged.
• Consistency means that the data meets all validity guidelines.
• Concurrency management is the primary objective of isolation.
• Durability ensures that once a transaction is committed, it will occur regardless of what happens in between such as a power outage, fire, or some other kind of disturbance.
2. What is the meaning of KPI in statistics?
KPI is an acronym for a key performance indicator. It can be defined as a quantifiable measure to understand whether the goal is being achieved or not. KPI is a reliable metric to measure the performance level of an organization or individual with respect to the objectives. An example of KPI in an organization is the expense ratio.
3. Explain One-hot encoding and Label Encoding. How do they affect the dimensionality of the given dataset?
One-hot encoding is the representation of categorical variables as binary vectors. Label Encoding is converting labels/words into numeric form. Using one-hot encoding increases the dimensionality of the data set. Label encoding doesn’t affect the dimensionality of the data set. One-hot encoding creates a new variable for each level in the variable whereas, in Label encoding, the levels of a variable get encoded as 1 and 0.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
#Python_Quiz
🚨CloudyML is giving PAID INTERNSHIP after course completion in Mega Combo Course Package.
Observed the given code below:
🚨CloudyML is giving PAID INTERNSHIP after course completion in Mega Combo Course Package.
Observed the given code below:
course_type="Data Science & Analytics Mega Combo"
if(course_type=="Data Science & Analytics Mega Combo"):
stipend=8000
elif(course_type=="Data Science Combo" or stipend=="Data Analytics Combo"):
stipend=5000
print('The Stipend Amount will be: ', stipend)Find out the correct stipend amount by solving the code above
Anonymous Quiz
21%
The Stipend Amount will be: 5000
72%
The Stipend Amount will be: 8000
6%
The Stipend Amount will be: 0
Date: 30-09-2022
Company name: Brookfield
Role: SQL Developer
Topic: Normalisation, Constraints, Database usecases
1. What is denormalization?
Denormalization is the opposite of normalization; redundant data is added to speed up complex queries that have multiple tables that need to be joined. Optimization of the read performance of a database is attempted by adding or grouping redundant copies of data.
2. What are the applications of SQL?
The major applications of SQL include:
• Writing data integration scripts
• Setting and running analytical queries
• Retrieving subsets of information within a database for analytics applications and transaction processing
• Adding, updating, and deleting rows and columns of data in a database.
3. What is a DEFAULT constraint?
A default constraint is used to define a default value for a column so that it is added to all new records if no other value is specified. For example, if we assign a default constraint for the E_salary column in the following table and set the default value to 85000, then all the entries of this column will have the default value of 85000, unless no other value has been assigned during the insertion.
4. What is an index in SQL?
Indexes help speed up searching in a database. If there is no index on a column in the WHERE clause, then the SQL Server has to skim through the entire table and check each and every row to find matches, which may result in slow operations in large data.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: Brookfield
Role: SQL Developer
Topic: Normalisation, Constraints, Database usecases
1. What is denormalization?
Denormalization is the opposite of normalization; redundant data is added to speed up complex queries that have multiple tables that need to be joined. Optimization of the read performance of a database is attempted by adding or grouping redundant copies of data.
2. What are the applications of SQL?
The major applications of SQL include:
• Writing data integration scripts
• Setting and running analytical queries
• Retrieving subsets of information within a database for analytics applications and transaction processing
• Adding, updating, and deleting rows and columns of data in a database.
3. What is a DEFAULT constraint?
A default constraint is used to define a default value for a column so that it is added to all new records if no other value is specified. For example, if we assign a default constraint for the E_salary column in the following table and set the default value to 85000, then all the entries of this column will have the default value of 85000, unless no other value has been assigned during the insertion.
4. What is an index in SQL?
Indexes help speed up searching in a database. If there is no index on a column in the WHERE clause, then the SQL Server has to skim through the entire table and check each and every row to find matches, which may result in slow operations in large data.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
🚨JOB OPENING ALERT FOR DATA SCIENCE & DATA ENGINEERING
Company Name: The Math Company
Exp: Min 2 Yrs
APPLY NOW - https://forms.gle/uEeCzWgHAZ5i44Jc6
Company Name: The Math Company
Exp: Min 2 Yrs
APPLY NOW - https://forms.gle/uEeCzWgHAZ5i44Jc6
Date: 01-10-2022
Company - MuSigma
Role- ML Engineer
Topic: sampling, law of large numbers, constructors, percentile
1.What are techniques used for sampling?
There are various methods for drawing samples from data.
The two main Sampling techniques are
-Probability sampling
-Non-probability sampling
Probability sampling:
Probability sampling means that each individual of the population has a possibility of being included in the sample. Probability sampling methods include –
-Simple random sampling:
In simple random sampling, each individual of the population has an equivalent chance of being selected or included.
-Systematic sampling:
Systematic sampling is very much similar to random sampling. The difference is just that instead of randomly generating numbers, in systematic sampling every individual of the population is assigned a number and are chosen at regular intervals.
-Stratified sampling:
In stratified sampling, the population is split into sub-populations. It allows you to conclude more precise results by ensuring that every sub-population is represented in the sample.
-Cluster sampling:
Cluster sampling also involves dividing the population into sub-populations, but each subpopulation should have analogous characteristics to that of the whole sample. Rather than sampling individuals from each subpopulation, you randomly select the entire subpopulation.
-Non-probability sampling :
In non-probability sampling, individuals are selected using non-random ways and not every individual has a possibility of being included in the sample.
-Convenience sampling:
Convenience sampling is a method where data is collected from an easily accessible group.
-Voluntary Response sampling:
Voluntary Response sampling is similar to convenience sampling, but here instead of researchers choosing individuals and then contacting them, people or individuals volunteer themselves.
-Purposive sampling:
Purposive sampling also known as judgmental sampling is where the researchers use their expertise to select a sample that is useful or relevant to the purpose of the research.
-Snowball sampling:
Snowball sampling is used where the population is difficult to access. It can be used to recruit individuals via other individuals.
2.How to get the minimum, 25th percentile, median, 75th, and max of a numeric series?
"randomness= np.random.RandomState(100)
s = pd.Series(randomness.normal(100, 55, 5))
np.percentile(ser, q=[0, 25, 50, 75, 100])"
3.What is _init_ in Python?
“_init_” is a reserved method in python classes. It is known as a constructor in object-oriented concepts. This method is called when an object is created from the class and it allows the class to initialise the attributes of the class.
4.Explain the Law of Large Numbers.
The ‘Law of Large Numbers’ states that if an experiment is repeated independently a large number of times, the average of the individual results is close to the expected value. It also states that the sample variance and standard deviation also converge towards the expected value.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company - MuSigma
Role- ML Engineer
Topic: sampling, law of large numbers, constructors, percentile
1.What are techniques used for sampling?
There are various methods for drawing samples from data.
The two main Sampling techniques are
-Probability sampling
-Non-probability sampling
Probability sampling:
Probability sampling means that each individual of the population has a possibility of being included in the sample. Probability sampling methods include –
-Simple random sampling:
In simple random sampling, each individual of the population has an equivalent chance of being selected or included.
-Systematic sampling:
Systematic sampling is very much similar to random sampling. The difference is just that instead of randomly generating numbers, in systematic sampling every individual of the population is assigned a number and are chosen at regular intervals.
-Stratified sampling:
In stratified sampling, the population is split into sub-populations. It allows you to conclude more precise results by ensuring that every sub-population is represented in the sample.
-Cluster sampling:
Cluster sampling also involves dividing the population into sub-populations, but each subpopulation should have analogous characteristics to that of the whole sample. Rather than sampling individuals from each subpopulation, you randomly select the entire subpopulation.
-Non-probability sampling :
In non-probability sampling, individuals are selected using non-random ways and not every individual has a possibility of being included in the sample.
-Convenience sampling:
Convenience sampling is a method where data is collected from an easily accessible group.
-Voluntary Response sampling:
Voluntary Response sampling is similar to convenience sampling, but here instead of researchers choosing individuals and then contacting them, people or individuals volunteer themselves.
-Purposive sampling:
Purposive sampling also known as judgmental sampling is where the researchers use their expertise to select a sample that is useful or relevant to the purpose of the research.
-Snowball sampling:
Snowball sampling is used where the population is difficult to access. It can be used to recruit individuals via other individuals.
2.How to get the minimum, 25th percentile, median, 75th, and max of a numeric series?
"randomness= np.random.RandomState(100)
s = pd.Series(randomness.normal(100, 55, 5))
np.percentile(ser, q=[0, 25, 50, 75, 100])"
3.What is _init_ in Python?
“_init_” is a reserved method in python classes. It is known as a constructor in object-oriented concepts. This method is called when an object is created from the class and it allows the class to initialise the attributes of the class.
4.Explain the Law of Large Numbers.
The ‘Law of Large Numbers’ states that if an experiment is repeated independently a large number of times, the average of the individual results is close to the expected value. It also states that the sample variance and standard deviation also converge towards the expected value.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS FROM SCRATCH. CHECK OUT OUR MEGA COMBO COURSE PACKAGE.
This course package, you are getting Python, R, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Chat Support Everyday and PAID INTERNSHIP. Check the course NOW!
Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo