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While slightly more than half of end users say spam isn’t a problem,

nearly 80 percent of IT managers say it’s a problem that they’re

struggling with, according to a new study.

But despite their difference of opinion of the situation today, both end

users and IT managers say it’s a problem that will plague them for years

to come.

”They really don’t have a positive outlook about this,” says Chris

Miller, director of product management for Symantec, Inc., an

information security company based in Cupertino, Calif. ”In some ways,

it’s almost like being on the Titanic. The iceberg has been hit and the

crew is aware of all the impacts. The passengers up on the deck don’t see the damage below and don’t know all the implications, so they think it’s a little more under control. But everybody knows it’s going to be a long night and there’s a lot more icebergs ahead.”

The study, conducted by Insight Express for Symantec, shows that overall

end users are a lot less concerned about spam than their counterparts in

the IT department.

Slightly more than 50 percent of end users surveyed say spam is not a

problem in their workplace. However, 79.1 percent of IT managers say it

is a problem in the workplace.

When end users were asked if they think spam is under control at their

company, 8.4 percent say it’s out of control; 23.3 percent say it’s

barely under control, and 68 percent say it is under control.

Compare that to IT administrators who were asked the same question. A

similar 10 percent say it’s out of control; 33 percent say it’s barely

out of control, and 56 percent say they have it under control.

”End users are experiencing some degree of respite from the amount of

spam they are seeing,” says Miller. ”But the IT administrators are

basically getting the brunt of this problem. They’re not just dealing

with one person’s spam. They’re dealing with the spam that’s coming in

to everybody.

”They’re dealing with bandwidth usage, storage usage, viruses it may be

bringing in, staffing and the hours they have to put in,” adds Miller.

”They’re spending a lot of time with this problem. The end user sees it

as garbage they have to deal with. The IT manager has a lot of other


In fact, the survey shows that spam has become one of the top worries

for administrators.

When IT managers were asked what they spend the majority of their time

on, spam came in second only to malware. Miller says 42.7 percent of

managers report malware as their worst problem, and 16.4 percent say

it’s spam.

”For a lot of our customers, I’d say it’s a nightmare,” he adds.

And it appears to be a nightmare that isn’t going away anytime soon.

According to the survey, 70.9 percent of IT administrators say they’ll

still be wrestling with spam three years from now, while 72 percent of

users say it will only get worse.

”This is painting a pretty grim picture moving forward,” says Miller.

”They’re both seeing increases and they’re both seeing it as a

long-term problem.”

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Understand Machine Learning And Its End

This article was published as a part of the Data Science Blogathon.

What is Machine Learning?

Machine Learning: Machine Learning (ML) is a highly iterative process and ML models are learned from past experiences and also to analyze the historical data. On top, ML models are able to identify the patterns in order to make predictions about the future of the given dataset.

Why is Machine Learning Important?

Since 5V’s are dominating the current digital world (Volume, Variety, Variation Visibility, and Value), so most of the industries are developing various models for analyzing their presence and opportunities in the market, based on this outcome they are delivering the best products, services to their customers on vast scales.

What are the major Machine Learning applications?

Machine learning (ML) is widely applicable in many industries and its processes implementation and improvements. Currently, ML has been used in multiple fields and industries with no boundaries. The figure below represents the area where ML is playing a vital role.

Where is Machine Learning in the AI space?

Just have a look at the Venn Diagram, we could understand where the ML in the AI space and how it is related to other AI components.

As we know the Jargons flying around us, let’s quickly look at what exactly each component talks about.

How Data Science and ML are related?

Machine Learning Process, is the first step in ML process to take the data from multiple sources and followed by a fine-tuned process of data, this data would be the feed for ML algorithms based on the problem statement, like predictive, classification and other models which are available in the space of ML world. Let us discuss each process one by one here.

Machine Learning – Stages: We can split ML process stages into 5 as below mentioned in the flow diagram.

Collection of Data

Data Wrangling

Model Building

Model Evaluation

Model Deployment

Identifying the Business Problems, before we go to the above stages. So, we must be clear about the objective of the purpose of ML implementation. To find the solution for the given/identified problem. we must collect the data and follow up the below stages appropriately.

Data collection from different sources could be internal and/or external to satisfy the business requirements/problems. Data could be in any format. CSV, XML.JSON, etc., here Big Data is playing a vital role to make sure the right data is in the expected format and structure.

Data Wrangling and Data Processing: The main objective of this stage and focus are as below.

Data Processing (EDA):

Understanding the given dataset and helping clean up the given dataset.

It gives you a better understanding of the features and the relationships between them

Extracting essential variables and leaving behind/removing non-essential variables.

Handling Missing values or human error.

Identifying outliers.

The EDA process would be maximizing insights of a dataset.

Handling missing values in the variables

Convert categorical into numerical since most algorithms need numerical features.

Need to correct not Gaussian(normal). linear models assume the variables have Gaussian distribution.

Finding Outliers are present in the data, so we either truncate the data above a threshold or transform the data using log transformation.

Scale the features. This is required to give equal importance to all the features, and not more to the one whose value is larger.

Feature engineering is an expensive and time-consuming process.

Feature engineering can be a manual process, it can be automated

Training and Testing:

the efficiency of the algorithm which is used to train the machine.

Test data is used to see how well the machine can predict new answers based on its training.

used to train the model.


Training data is the data set on which you train the model.

Train data from which the model has learned the experiences.

Training sets are used to fit and tune your models.


learnt good enough from the experiences it got in the train data set.

are “unseen” data to evaluate your models.

Test data: After the training the model, test data is used to test its efficiency and performance of the model

The purpose of the random state in train test split: Random state ensures that the splits that you generate are reproducible. The random state that you provide is used as a seed to the random number generator. This ensures that the random numbers are generated in the same order.

Data Split into Training/Testing Set

We used to split a dataset into training data and test data in the machine learning space.

The split range is usually 20%-80% between testing and training stages from the given data set.

A major amount of data would be spent on to train your model

The rest of the amount can be spent to evaluate your test model.

But you cannot mix/reuse the same data for both Train and Test purposes

If you evaluate your model on the same data you used to train it, your model could be very overfitted. Then there is a question of whether models can predict new data.

Therefore, you should have separate training and test subsets of your dataset.

MODEL EVALUATION: Each model has its own model evaluation mythology, some of the best evaluations are here.  

Evaluating the Regression Model.

Sum of Squared Error (SSE)

Mean Squared Error (MSE)

Root Mean Squared Error (RMSE)

Mean Absolute Error (MAE)

Coefficient of Determination (R2)

Adjusted R2

Evaluating Classification Model.

Confusion Matrix.

Accuracy Score.

Deployment of an ML-model simply means the integration of the finalized model into a production environment and getting results to make business decisions.

So, Hope you are able to understand the Machine Learning end-to-end process flow and I believe it would be useful for you, Thanks for your time.


How To Send Spam Calls Straight To Voicemail On Android

It’s probably safe to say that most people don’t put much thought into the dialer app on their phones. Open it up, punch in a number and dial away — pretty straightforward, right?

Given the relative simplicity of the app, it’s kind of surprising to learn that Google has been quietly working on a Dialer app for a number of years now. So just what does Google think they can improve? As it turns out, Google has been trying to do eliminate a modern annoyance that virtually everyone with a phone has had to learn to live with: automated telemarketing.

Whether you call them robocalls, autodialers or spam calls, automated telemarketing calls have increased sharply in the past few years. According to the Federal Trade Commission, 375,000 complaints were lodged every month of 2023. Compare that to the 65,000 per month they received back in 2009, and its no surprise Google is trying to alleviate the problem.

What Does the Google Phone App Do?

Google stepped up its fight against automated telemarketing calls back in 2024. This is when the Google Phone app started warning the use of suspected robocalls by turning the screen bright red and listing the caller as “Suspected Spam Call.” Unfortunately, the call still came through, and users had to decide whether to answer or not.

In the updated version of the app, you won’t even be notified that the call came through at all. No ringing, no bright red screen, no notification. Almost like the call didn’t come through at all. Instead, Google Phone will filter any suspected robocalls straight to voicemail. Of course, you’ll still be able to review all the calls that come through via your call history. Additionally, if the spam caller leaves a voicemail, it will still be recorded to your voicemail bank.

How to Install the Google Phone App

The Google Phone App comes as the default dialer on the Pixel, the Nexus and Android One devices. Unfortunately, at the time of this writing, the app has not been made available to the general public. That being said, it is possible to get the Google Phone App on your device. To do so, you’ll need to become a beta tester of the app.

Be aware that since the updated version of the Google Phone app is still in beta, there’s a good chance there will be a few bugs that still need to be ironed out. Furthermore, the app is not compatible with all devices at this time. If you are not able to download the app due to your device being flagged as “not compatible.” you can email the Google Phone development team for support.

How to Turn on the Robocall Filter

Be aware that robocalling techniques are getting more and more sophisticated. Unfortunately, this means that the Google Phone app won’t necessarily catch every single telemarketing call that comes through. For instance, it has been reported that robocalls that utilize “neighborhood spoofing” usually get through. This is when the robocall originates from a number with the same area code as your own.

What to Do If You Can’t Install Google Phone

Unfortunately, Google Phone is not available for every Android device out there. If you find that your device is not compatible with the app, don’t fret. The inability to install Google Phone doesn’t mean that you’re destined for annoying robocalls. There are a number of apps that can stop robocalls, and many of them are free like Hiya and Mr. Number. Additionally, many of the cell phone providers in the United States offer apps specifically for phones that use their networks, so check with your carrier.

Finally, if you haven’t done so already, add your number to the National Do Not Call Registry. It’s free and you can do it online, so there’s really no excuse not to. It won’t stop all of the telemarketing calls, but it helps. Furthermore, you can always file a complaint with the FCC for those robocalls you can’t seem to shake.

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Avoid Spam And Junk Mails Using Anonymous Email Forwarding

Avoid Spam and Junk Mails using Anonymous Email Forwarding

What is Spam Filtering?

Spam Filtering is the process of identifying and getting rid of Spam and potentially malicious emails created to loot you. There is no straightforward way to deal with Spam and Malicious emails.

Email Filtering is the process of Organizing various mails categorically according to their purpose and use. This helps manage all the information that you have on your email and makes it easier to find when needed.

What is Anonymous Email Forwarding?

Now Amazon doesn’t know who you are because your Email address doesn’t tell anything about you, hence, the word ANONYMOUS.

Anonymous Email Forwarding has various benefits, including effective Spam Filtering and Email filtering. Let’s move forward to the next section and discuss the Advantages of using Anonymous Email Forwarding.

Also Read: Tips to Improve your Email Security

Benefits of Anonymous Email Forwarding:

Anonymous Email Forwarding has many benefits such as:

You stay Anonymous on the web which is an actual need of the hour in the current

Easily you can Manage all your emails from various sources without having to manually classify them in different categories.

You can deal with Spam Emails once and for all using Anonymous Email Forwarding.

Get full control over your data and emails that you receive.

Having Anonymous Email Forwarding through a different alias of yours provides your protection against hackers too. For example, a hacker gets a hold of one of your email aliases. You can simply close that Email Alias by logging into the parent account.

Having considered all the awesome benefits of using Anonymous Email Forwarding, let’s continue to how you can use and set up Anonymous Email Forwarding.

Also Read: How to Encrypt Emails to Level up your Email Security?

How to Setup Anonymous Email Forwarding?

Any user wanting to setup Anonymous Email Forwarding has to sign up for a service that provides the facility of setting up aliases.

Two major service providers allow you set up email aliases – AnonAddy and SimpleLogin. Both these companies offer both Free and Paid plans.

For an individual, the free plans are enough. You can create 20 different aliases using the free plan of AnonAddy and 15 different aliases using the Free plan of SimpleLogin.

How to Stop Spam Mails and Junk Mails using Anonymous Email Forwarding?

Email Forwarding through Aliases provides the solution to your problems with Anonymity, Spams, and Junk. All you have to do is to be a bit creative. You can create multiple aliases for all the different purposes.

Let me tell you how I do so:

Now, only provide your work email address to the people who work with you, streaming email address to streaming sites only, Social email to social accounts only, and Family Email to Family people. Now all the emails that you receive for promotional purposes will be in your Social Account, Streaming Account, and IDontCare account.

Whenever you log into your account you will be able to see the emails already classified according to the aliases on which the email is received. You can choose to view only the Family and Work Account and ignore everything else. Your Family Email and Work Email won’t have any random spam email in them. The emails that you receive on other aliases can be easily ignored because you know there won’t be any important informational emails over there.

Next Readings:

Essential Features Of An Email Forensic Tool

How to Send Anonymous Emails: 5 Methods

Best Email Backup Software For Windows 2023

How to Save a Backup of Your Emails in Gmail

Quick Reaction:

About the author

Sagar Kapoor

Examples And Nested Begin & End Keyword Usage

Introduction to Begin SQL

Begin SQL is the keyword that is used to mark up and specify the beginning of the transaction or stored procedure or functions or simply the collection of multiple statements inside the logical block whose body starts from the specification of the BEGIN keyword and stops with the use of END keyword. We can write the sequence of the statement that we wish to execute inside the BEGIN and END keywords in SQL. Multiple BEGIN END statements can be written inside the same method or stored procedure, etc. We can even write nested BEGIN END statements in SQL where the logical block of statements defined between BEGIN and END keywords can be executed on a conditional basis or inside the loops and other functions according to the use case and requirement.

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In this article, we will learn about the syntax of using the BEGIN keyword in SQL and the END keyword that helps create a logical block of SQL statements with the help of syntax and few examples.


The following is the syntax of using the BEGIN keyword in SQL, which is accompanied with END for termination of the block of statements –


The use of BEGIN is mostly done in Transact-SQL, where multiple statements are executed completely in a transactional manner to maintain the consistency of the database operations and ACID properties of the database. We can mention the statements that we want to execute in a transactional manner inside the BEGIN and END keywords, as shown in the above syntax. The statements inside the BEGIN and END are also known as the batch that is executed together. We can mention the set of statements of SQL inside the BEGIN and END keywords.

Let us consider a few of the examples that will make the implementation of BEGIN in SQL clear to you.

Examples of Begin SQL

We will consider one existing table named students that are present inside the database named educba on my SQL server. The structure and contents of the table students can be seen from the output of the following query statement –

SELECT * FROM students;

The output of the execution of the above query statement is as follows –

The students’ table contains 14 records in it. Now, we want to execute three statements in the transact SQL that includes the addition of two records named Karna and Yudhishthira to the students’ table and, upon addition, retrieval of the records of the students’ table. We will place our SQL query statements of INSERT and SELECT queries inside the BEGIN and END keyword as shown in the below code –

BEGIN INSERT INTO `students` (`student_id`, `class_id`, `name`, `roll`, `technology`, `percentage`) VALUES('15','3','Karna','Manager','Maven','96%'); INSERT INTO `students` (`student_id`, `class_id`, `name`, `roll`, `technology`, `percentage`) VALUES('16','2','Yudhistir','Administrator','MySQL','92%'); SELECT * FROM students; END

The output of the execution of the above query statements and block is as follows –

We can observe that the two additional records have been inserted into the students’ table, and now, the students’ table contains 16 records in total that are retrieved from the third SELECT query that we mentioned in our logical block between BEGIN and END keywords.

Let us now consider one more example in which we want to get the records of the student’s names and id that have a percentage greater than 92, and if no records are retrieved, then it should give the output as ‘No students found that have achieved percentage greater than 92’. For this, we will first select the records from the student’s table that will have a percentage greater than 92 using the select query, and then if the row count of the retrieved query is zero, then we will select the string literal value that will contain the sentence as required when no such record is found.

We will use the IF statement to check the row count condition and will place all these statements inside the BEGIN and END to make them a single logical block that will consist of our statements as shown below –

BEGIN SELECT student_id, NAME FROM educba.students WHERE IF @@ROWCOUNT = 0 SELECT 'No students found that have achieved percentage greater than 92'; END

The output of the execution of the above query statements and block is as follows –

Nested BEGIN and END keyword usage

We can even make the use of nested BEGIN END blocks inside each other and create different logical blocks of statements to be executed. The BEGIN and END togetherly work as { and } in C, JAVA, or any other language. We can execute these logical blocks based on some conditions and also repetitively inside various looping statements of SQL.

Let us consider one simple example of nested BEGIN END blocks in SQL that will retrieve the name of the students that are ordered in the descending manner of their percentages and then get the value of the first record from the query that retrieves the names of students and stores the name of the student with the highest percentage inside the variable named @name. Further, we want to check if the row count of the result set of the query statement is not equal to zero, then print the value of the name in the string ‘The highest scoring student is the name of student else execute another block of BEGIN END that will get the string value ‘No student found’. We will use the following code for that –

BEGIN DECLARE @name VARCHAR(100); SELECT @name = NAME FROM educba.students ORDER BY percentage DESC; BEGIN SELECT 'The most highest scoring student is ' + @name; END ELSE BEGIN SELECT 'No student found'; END; END

The output of the execution of the above query statements and block is followed, retrieving the name of student Karna that has the highest percentage that is 96% –


We can make the use of the BEGIN keyword in SQL to mark the starting point of the logical block of statements of transact SQL that we need to specify and use the END keyword to specify the closing point of a logical block in SQL.

Recommended Articles

We hope that this EDUCBA information on “Begin SQL” was beneficial to you. You can view EDUCBA’s recommended articles for more information.

The Fcc Is Trying To Crack Down On Those Annoying Spam Texts

“As the FCC continues to combat unwanted robocalls, it recognizes that it must adapt to the latest scamming trends— including the rise of robotexts,” the FCC said in a statement, adding that they received around 14,000 consumer complaints about unwanted text messages in 2023 alone—nearly a 146 percent increase from the year prior. And in 2023, the Commission has already reported more than 9,800 complaints about spam texts. During COVID-19, for example, the FCC warned against package delivery notification scam calls and texts. 

The Commission also cited data collected by spam call blocking app RoboKiller, which reported 7.4 billion spam texts in March 2023.

[Related: Congress is coming for big tech—here’s how and why]

The proposal, which would be adopted if it received a full vote from the Commission, would explore different approaches to protect consumers from illegal robotexts, including having mobile carriers block these texts at the network level, and using caller ID authentication on messages. 

While this proposal is in regards to texts, federal authorities have been fighting against robocalls since 2009, according to the US Public Interest Research Group. That year, the Federal Trade Commission made pre-recorded telemarketing calls illegal. In 2024, AT&T, Apple, Comcast, Google, Verizon, along with dozens of other technology and communications companies, agreed to work with the FCC to crack down on robocalls, Reuters reported. 

The FTC wrote in February that consumers reported losing nearly $3.3 billion to frauds in 2023, with phone calls and text messages listed as the top ways scammers are reaching them. 

[Related: Cryptocurrency scammers are mining dating sites for victims]

In recent years, the Commission has spent over $450 million to enforce legal actions against telemarketers. This year especially, the FCC is doubling down on its efforts to prevent robocalls and texts from entering the US phone networks. In June, the Commission mandated that phone companies such as AT&T, Verizon and T-Mobile use caller ID authentication to identify who’s calling you, and in September, the Commission announced that calls from numbers not listed in its Robocall Mitigation Database will now be blocked on US phone networks. 

But scammers are tricky to stop. And not even 911 call centers are safe from phone scammers. “It’s a game of Whac-A-Mole,” Paul Schmitt, a research computer scientist at the University of Southern California’s Information Sciences Institute, told CNBC in September. “Robocallers will find other ways to do what they want to do.” Further, CNBC said that “robocalls reel in billions of dollars in profits every year.”

[Related: The FCC wants to know if you’re paying too much for internet access]

Tejas Narechania, faculty director at the Berkeley Center for Law & Technology, says via email that while this new proposal is a good start, “we’ve seen in the robocall context that this is a hard issue to address.” 

He notes that it will be key to look for the regulatory details around these new rules and how they will be implemented. “The rules propose things like authentication standards, that we’re starting to see implemented in the robocall context, and that have started to have some effect,” he says. “But it’s cheap for fraudsters to send out millions of these messages (often from abroad), and it can be lucrative to do so, so I don’t think this is going to solve everything.”

Moreover, these rules apply to text messages, but not to fraudulent messages sent over other platforms, such as WhatsApp, he adds. “We’ll need more action in order to fully address this problem.”

To help consumers, the FCC has issued guides on avoiding unwanted spam calls and texts, which include tips such as not picking up on calls from unknown numbers, or hanging up quickly without responding or engaging. For texts, the FCC suggests that you immediately block the sender or report the message as spam to your mobile provider. (Verizon, for example, lets users forward the message to 7726, or SPAM, to block and report the sender.) In general, consumers should be wary about giving out their personal info and phone number, or opting into receiving text messages through commercial web sites. 

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