INTERESTING QUOTES ABOUT JAVASCRIPT

JavaScript is the most widely deployed language in the world.

Whether you're intrested in writting client-side or server-side code or even game development, you'll be able to accomplish all of this and more with JavaScript.

This learning path includes JavaScript tutorials for both the new programmer looking to get started and the advanced developer wanting to solidify and3 enhance their skills. 

Interesting Quotes About JavaScript

The strength of JavaScript is that you can do anything. The weakness is that you will!                                                                                        By- Reg Barithwaite

As a Lead JavaScript Engineer, I try to get my team to write as little JavaScript as possible!                                                                                 By- Anonymous

 Anything that can be written in JavaScript, will eventually be written in JavaScript!                                                              By- Jeff Atwood

If you are choosing a JavaScript library purely based on popularity, I think you deserve what you get!                                                           By- Tom Dale

JavaScript is the only language that i'm aware of that people feel they don't need to learn before they start using it!                                               By- Douglas Crockford

Always bet on JavaScript                                          By- Brendan Eich

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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.

SOPHIA, The Humanoid Robot

As we all know, the field for AI and robotics is very fast-growing. Now robots can perform movement like- back-flipping, practicing parkour moves, and even classical sculptures.

Sophia is  human-like robot, created by Hanson Robotics. Sophia is very advanced robot. Sophia was first activated on February 14, 2016, and her public appearance at South by Southwest Festival(SXSW) in March 2016 in Austin, Texas, US.

Sophia is able to display more than 50 facial expressions.

The founder of Hanson Robotics, David Hanson said "We're not fully there yet, but Sophia can represent a number of emotional states, and she can also see emotional expressions on a human face as well,"

According to Hanson, Sophia now has simulations of every major muscle in the human face, allowing her to generate expressions of joy, grief, curiosity, confusion, contemplation, sorrow, frustration, among other feelings. She is human-crafted science fiction character depicting where AI and robotics are heading. In other ways, Sophia is real science, springing from the serious engineering and science research and accomplishments of an inspired team of robotics & AI scientists and designers.

"In some of the work we're doing, she will see your expressions and sort of match a little bit and also try to understand in her own way, what it is you might be feeling," says Hanson.

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
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Written by Aakash deep gupta

FIVE TECH TRENDS FOR 2019

Five Tech Trends for 2019

1. Artificial Intelligence

Within a few years, analysts predict that all software will use AI at some level, according to US research and advisory firm Gartner.

2. Augmented Reality

Organizations are increasingly applying this technology across a wide spectrum of human activity from art and entertainment to commerce, education and the military.

 3. Block Chains

The fortunes of digital currency Bitcoin have drawn public attention to Blockchain technology, but this secure system for recording and verifying transactions and storing trusted records has the potential to disrupt enterprise of many kinds.

4. Automation

From convenient devices at home to industrial applications on a massive scale, automation will be a key focus of technological change, with potentially far-reaching economic and social consequences.

5. Internet Of Things

It is early days for the application of IoT strategy but it is clear that opportunities will exist for those with the technical knowledge to connect platforms as well as those with the data analytics skills to utilize the rich stream of information generated by IoT application.

Written by- Aayush Sourav

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