WHAT IS DUCKDUCKGO AND WHY YOU SHOULD BE USING IT

What is DuckDuckGo and Why You Should Be Using It?

DuckDuckGo is a search engine that, unlike Google, tries to protect the privacy of its users, by deliberately showing all users the same search results for a specific keyword, without filtering those search results and personalizing them based on the history of the user.

What DuckDuckGo does that Google does not 

1. It does not store the IP address of its user.

2. DuckDuckGo does not log any user related information. only keyword-related information.

3. It includes data from a compilation of over 400 sources, including Bing, Wolfram Alpha, Wikipedia, Yahoo!, its own web crawler, called the DuckDuckBot, and many others.

4. It uses cookies only when needed.

The benefits of using DuckDuckGo, for users

1. User privacy. There is no personal information collected and stored about users. There is no search history stored for you as a user.

2. It prevents search leakage. The websites that you visit from DuckDuckGo do not know what you searched for, to get to them.

3. Transparency about how it works and how it treats users. If you want you can contribute to DDG by submitting translations, features ideas, bug reports, etc.

How does DuckDuckGo make money?

This search engine earns money by serving ads through the Microsoft/Bing/Yahoo ad network, as well as through affiliate marketing, in partnership with Amazon and eBay. It displays generic ads for your search, without tracking you or fine-tuning ads to make them more targeted and desirable for you to click. Also, the number of ads displayed by DuckDuckGo is smaller than what you see on Google.

Understanding Reinforced and Semi supervised Machine learning

Article 1:Iintroduction to Artificial intelligence and Machine learning

Article 2:Introduction To Machine Learning Algorithm
article 3:Understanding Supervised and unsupervised machine learning

Understanding Reinforced and Semi supervised Machine learning

As we already discussed the first two types of Machine learning Algorithm its time to understand next two and final types of machine learning algorithm which are:

*Semi supervised Machine learning
*Reinforced Machine Learning

Review of Supervised and Unsupervised Machine learning.

Supervised Machine learning:

In supervised machine learning ,system is trained using training data or also labeled data or also classified example modal .algorithm uses these training data to take decision and show results ,this type of algorithm is very time consuming and expensive but more accurate.

Unsupervised machine learning:

In unsupervised machine learning ,system is trained without any labeled data or also classified data or also example modal. These type of algorithm is less time consuming and expensive but less accurate.

What is semi supervised machine learning?

Due to use of a lot of labeled data ,supervised learning is very time consuming and expensive,in some experiment data scientists used some labeled data with some unlabeled data and founded that it increases the accuracy of result and it was easy to implement than supervised learning. And more accurate than unsupervised learning.
         Hence they devloped a new algorithm which falls between supervised and unsupervised learning aka,semi supervised learning.
       Semi supervised learning involves human agent to render data and modals .
       

As we now know what is semi supervised learning we can now try to understand  About Reinforced machine learning..

What is Reinforced machine learning?

Reinforced learning is a technique to train a program using trial an error method or more practical way as human learns from environment using their actions.

For example if a kid does something good gets a choclate as a reward and  for doing something bad gets scolded by their parents.
      Reinforced learning is also based on same principal if system does something valuable gets reward points by agents but when it does something value less ,reward point is reduced .
System used these past experience to learn and be accurate .
        So simply this technique is more action based and trained under live environment , this topic is very eye catching for research among data scientists and programmers due to its possibility in future to create a very advanced independent system.
       In next we will discuss more about these technique and terms related to Artificial intelligence .

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Written by- Aakash deep gupta 

Understanding Supervised and Unsupervised Machine Learning

Understanding supervised and unsupervised machine learning.

Article 1:Iintroduction to Artificial intelligence and Machine learning
Article 2:Introduction To Machine Learning Algorithm
In previous Articles we Discussed, What is Machine learning ?

What is Machine learning Algorithm?

Now its time to discuss about different types of Algorithm used in Making intelligent programs ,
In general there are four types of ML algorithm :-

1.Supervised Learning.

2.Unsupervised Learning

3.Semi Supervised Learning

4.Reinforced Learning 

1. What is Supervised Learning?

Supervised Learning is a method of creating intelligent program by providing them Example data
Or Training Data which includes parameters and possible output . And these program use this Training data to generate result on Real given input.
      Its confusing? let us explain , for example you have to  classify four kinds of shape namely Square ,Rectangle ,Circle and Triangle . And these four shapes belongs to Two types of colours Blue and yellow .
         We uses parameters like radius ,sides ,colours to determine the shapes .

Square and circle belongs to blue while rectangle and triangle belongs to yellow.
Now we specified some properties

   Now we feed the example data or training data as,

A  blue circle
[Radius,blue,]

A blue Square
[Sides 4,blue]

A yellow rectangle
[Sides 4,yellow]

A yellow triangle
[Sides 3,yellow]
Now we wants to determine name of a unknown shape having known sides and colour.

Feed inputs to system
As [parameters,|possible output]
For example
   [4 sides,yellow|circle,square,rectangle,triangle]

Algorithm will check for parameters, as

It has 4 sides,
It can be square or rectangle

It has a color yellow
It can be triangle or rectangle

After calculation of mathematical values it will declare result
As Its A rectangle!

Hence ,supervised machine learning is a way in which we provide possible output and parameters to system to match it from training data .


Now we will try to understand the core concept of unsupervised machine learning.

2.What is unsupervised machine learning?

Unsupervised learning is method of creating intelligent programs by providing it Only imputs as parameters but not any example model.
      We can also say that the output of the data is unknown ,and  its algorithms responsibility to determine the shape by it self.


Let me explain using previous example .

In this case we will provide inputs in this manner
     As   [Parameters],
For example
          [4 sides ,yellow]

In this case system will use its intelligent algorithm to determine the name of shape by it self .


I hope that ,you now understands the basic concepts and difference between supervised and unsupervised machine learning .
Next article will deal with next two types
3.semi supervised learning
4.reinforced learning

Thank you
If you want to join our official telegram channel, click here

Written by Aakash deep gupta

UNDERSTANDING MACHINE LEARNING ALGORITHM

Understanding Machine learning Algorithm

Article 1:Iintroduction to Artificial intelligence and Machine learning

As We Already know, What is Machine Learning  in previous article  or subset of Artificial Intelligence .

          We can now proceed to more complex topics in this Series . The next topic we are going to discuss is Machine learning Algorithm .which deals with the method and logic's behind these intelligent systems.

                But before machine learning algorithm we  must understand what this term Algorithm actually means in detail .

What is Algorithm?

In definition :

Algorithm is the set of Rules To be followed to solve a particular class of problems .

In general:
Algorithm is the steps involved in a process , which must be taken to find the solution of a particular types of  problem ,

For example :
Your mother asks you to bring milk from your uncles house so that she can prepares sweet from it and again asks you to deliver it to your uncles house.

Now let us convert it into Algorithm and a Program logic.

Step 1:
Take a empty bottle and go to uncles house.
Step 2:
Fill the bottle with milk
Step 3:
Travel to your home ,and give it to your mother.
Step 4:
Sweet is prepared by your mother
Step 5:
Deliver it to your uncles house.

What ? We were not talking about milks and sweets but Algorithm isn't it?
Now see the program version of the example.

Step 1:
You created a empty variable(bottle) and gave a message to user to give input(milk)

Step 2:
You took the input (milk) into variable(bottle)

Step3:
You presented it to processor (mother) it used the logic (Prepare the sweet)

Step 4:
Input (milk)  is now converted into output (sweet).

Step 5:
You gave the output (sweet) to user (uncle)
Explanation:
Let us assume we are making a program to check the no to be prime or not  We first creates a variable to store the number. Then we prints a message to input a number ,after that we apply the logic on number and prints the result to user
         All the individual steps involved is nothing but algorithm.

In programming the Algorithm is represented using Flow charts.

Now you understands the Term Algorithm . Now we will discuss ML algorithm.

What is Machine learning Algorithm?

Machine learning algorithm is the set of rules or methods of programming.
 in which program is written in a way that ,it can take inputs and can give the desired output without changing the program codes. It can use the input data to maximise the accuracy every time we provide  data.
      Or we can say that ,the steps and method we use to make program that is ,capable of receiving input , and changing  its code according to inputs data to increase the accuracy of desired output is known as machine learning algorithm.

The four types of Machine learning Algorithm are
1.Supervised learning

2.Unsupervised learning

3.semi supervised learning

4.Reinforced learning

We well discuss each of them in detail in next articles.

Thank you

Written by Aakash deep gupta

Beginner's Guide To Artificial Intelligence and Machine Learning : Introduction

beginner's Guide To Artificial Intelligence and Machine learning :Introduction

We cant deny the fact that nowdays sci-fi movies are more popular than any other genre also these amazing movies played a crucial role in growth of sci lovers . According to some theory   the master piece Interstellar inspired astrophysicist to research about black holes resulting in more proved theories.
       I am sure if you are a sci -fi fan you  definitely know at least a something about  Machine learning . This article is about to introduce you to machine learning ,its application and its dangers.

What is Machine learning?

Machine learning is a branch of Algorithm and programming in which we try to develop some advance system that can analyse data and can learn by it self .
       To be familiar with machine learning you may know what intelligence actually means and how brain works so lets begin.

What is intelligence ?

Intelligence in human beings is defined as

the ability to acquire and apply the knowledge

Acquiring knowledge is all about to collect the needed information and ,applying means to take decision on the basis of past experience ,learning and already Developed logic's.
Some examples are:


1.learning 

2.taking decision based on past good or bad experience.

3.mastering the technique to control your flow of emotions also termed as emotional intelligence .

Now you have a basic understanding of human intelligence so now we will discuss how brain works for intelligence.

How brain works?

In Human brain there's a kind  of cells cells that carry data we acquire called as neurons . These neurons have different kind of data each and when we try to learn something new or any mental activity, these neurons interact with each other to make new connections .
       You can understand it as ,we have all letter in different boxes (existing neurons ),and we take some letters and build some words and (some more neurons ) after that we connect those words and form  sentence (new connection)

Machine learning which is also called A subset of Artificial intelligence ,is based on similar principal .

Basic Theory

In machine learning or Artificial intelligence The program is build in a way that every time we feed data ,program build more accurate connection ,until it reach the most accurate result or it learns.

Why we need Artificial Intelligence?

The limit of computer is ,it can only solve those problems that human did already . In another word all the problem solved by computer are actually feeded by some intelligent programmer ,computer is actually not solving the problem but following the instructions.

But in artificial intelligence ,computer can try new logic's by themselves and can solve more complex problem a human cant even think of . Which gives it a value . A more interesting thing is it can analyse data and can conclude with accurate and valid results.

It was a basic introduction to artificial intelligence ,in next articles we will discuss Application ,terms related to AI , how it actually works and Dangers of AI .
Article 2:Introduction To Machine Learning Algorithm
Thank you.

Written by Aakash deep gupta

TYPES OF COMPUTER VIRUS

A computer virus is a malicious program / software that copy itself into another program. The purpose of creating a computer virus is to infect vulnerable system, gain admin control and steal user sensitive data. It is quite easy and simple for the virus to sneak into a computer by dodging the defense system.

Types of Computer Virus

1. File Virus

This type of virus infects the system by appending itself to the end of a file. It changes the start of a program so that the control jumps to its code. After the execution of its code, the control returns back to the main program. Its execution is not even noticed.

2. Bool Sactor Virus

It infects the boot sector of the system, executing every time system is booted and before operating system is loaded. It infects other bootable media like Floppy disks. These are also known as memory virus as they do not infect file system.

3. Encrypted Virus

In order to avoid detection by antivirus, this type of virus exists in encrypted form. It carries a decryption algorithm along with it. So the virus first decrypts and then executes.

4. Multipartite Virus

This type of virus is able to infect multiple parts of a system including Boot Sector, Memory and Files. This makes it difficult to detect and contain.

Armored Virus

An armored virus is coded to make it difficult for antivirus to unravel and understand. It uses a variety of techniques to do so like fooling antivirus to believe that it lies somewhere else than its real location or using compression to complicate its code.

Written by - Aayush Sourav

THREE LAYERS OF THE WEB

Three Layers Of The WEB

The Surface WEB

It's the common internet everyone uses to read articles, news, shop gadgets etc. If we want to find some information we search them which leads us to a website which is in surface web i.e indexed page visible to search engines.

How to Access?

Just search something in any search engine, it is a surface web, even google is a part of surface web.

The Deep WEB

The deep web is a sebset of the internet that is not indexed by the major search engines. This means that you have to visit those place directly instead of being able to search for them. So the Deep Web is the long tail of what's left out, like some company's database (as only specific people can access it)[not to be confused for internet, its another thing]

Also read:Ways to avoid being Hacked

How to Access?

You will require exact address or URL as these pages are not indexed and can't be searched.

 The Dark WEB

The Dark Web is a subset of the Deep Web that is not only not indexed, but that also requires something special to be able to access it, ex.- specific proxying software or authentication to gain access  (like TOR ). They are often associated with criminal activity of various degrees, including buying and selling drugs, gambling, etc.

Also read:Top 5 Indian Hackers

How to Access?

1. Download and install TOR browser.

2. Open TOR browser and clicks on onion icon.

3. Wait for some time once you securely connected you can see a green onion shaped icon.

What does each layes contain?