Is Machine Learning similar to Data Mining

 Plus/minus, positive/negative, True/False, and 0/1 these all are the concept of binary outcomes in the form of result which are normally used in Machine learning, Data mining using related programming languages. Today the user around the globe using different application which are based on Artificial Intelligence, and related smart machines. These  machines are so smart and  accurate for prediction and assumption in the form of IOT, AI base Robot and others. In the field of Data Science Machine learning and Data mining, these are the core field to find the knowledge base pattern from the existing data/database, for a long time smart machine based software has these features to make smart to smartest machines, but only few of folk know about the differences between these two very similar word Machine learning AND Data Mining!

   Majority of them thinking both are same because almost different algorithm like (Regression, Classification) are exist in both.

Fahad Hussain Tutorial CLICK here.

  So, in this Article we are going to understand about the differences and scope of Machine learning and Data Mining
Here we go!

Machine Learning:
  Machine learning is the subpart of Artificial Intelligence also include in the latest trending field of Data Science, So, what is ML: Machine learning is the study of powerful algorithm and statistical model that increase the ability of computer in term of working/performance without using explicit instruction, where ML divided into three parts:

 Supervised Learning
 Unsupervised Learning
 Reinforcement Learning

   Supervised Learning is the field for labeled data for predication and classification them using Regression and it different types, and classify using different ML Algorithm like (SVM, RF etc...). Unsupervised Learning is the field for unlabeled data for predication and clustering them using  different types of clustering, Algorithm like (SVM, RF etc...), whereas in Reinforcement learning the ability of learning is going to move ahead here we train out machine using plenty to avoid mistake again by using these technique machine able to work smart than before.

   The journey of Machine learning shows it is the collection statistical model base algorithm to make you machine smart in term of prediction and analysis. ML is not a new technology, first introduced in 1950 till now a lot of modern algorithms make their place in ML domain. ML used in different domains as well like Fraud Detection, Data Analysis, and many more.


Data Mining:
  Data mining (DM), is the process of finding/Discovering the designing pattern from large amount of data set by using different algorithm including the machine learning, statistical and database, therefore it is also called knowledge discovery in databases (KDD).

  In simple word, in this process we are finding those data set which is invisible but inherited from actual data set that is accurate and useful for us after discovering.It is an iterative process of creating a predictive and descriptive model, by uncovering previously unknown trends and pattern in vast amounts of data in order to support decision making. Also, DM applied in the limited area than machine learning because its domain big. Quite often, the data set in Data Mining is massive, complicated, and/or may have special problems (such as there are more variables than observations).

  Now it is time to compare them in term of working, performance and importance':


1.  It is used for extracting knowledge/information and describing about pattern on it from a big amount of data WHEREAS it is used to predict discrete/continuous value using different statistical and modern algorithm.

2.  The concept of Data Mining introduced in 1930 WHEREAS it is introduced in 1950.

3.  Its origin based on unstructured data/data set WHEREAS it is not necessary only unstructured data will be use.

4.  Generally used to identify the classification and clustering between/among different pattern WHEREAS it is not only used for that purpose also for fraud deduction, spam mail, disease identification etc.

5.  It is based/abstracted from Data warehousing that's why another course named Data mining and data warehousing also offered in BS/MS program of CS, WHEREAS it is based on data/machine.

6.  The scope or domain of Data Mining is not enough than Machine learning WHEREAS its area is vast in term of usage.



Author, Fahad Hussain   MSCS, MCS
Fahad Hussain Tutorial CLICK here.
      Voluntary work as a Computer Scientist, to explore the difficulties as simple words!!!

Is Machine Learning similar to Data Mining

 Plus/minus, positive/negative, True/False, and 0/1 these all are the concept of binary outcomes in the form of result which are normally used in Machine learning, Data mining using related programming languages. Today the user around the globe using different application which are based on Artificial Intelligence, and related smart machines. These  machines are so smart and  accurate for prediction and assumption in the form of IOT, AI base Robot and others. In the field of Data Science Machine learning and Data mining, these are the core field to find the knowledge base pattern from the existing data/database, for a long time smart machine based software has these features to make smart to smartest machines, but only few of folk know about the differences between these two very similar word Machine learning AND Data Mining!

   Majority of them thinking both are same because almost different algorithm like (Regression, Classification) are exist in both.

Fahad Hussain Tutorial CLICK here.

  So, in this Article we are going to understand about the differences and scope of Machine learning and Data Mining
Here we go!

Machine Learning:
  Machine learning is the subpart of Artificial Intelligence also include in the latest trending field of Data Science, So, what is ML: Machine learning is the study of powerful algorithm and statistical model that increase the ability of computer in term of working/performance without using explicit instruction, where ML divided into three parts:

 Supervised Learning
 Unsupervised Learning
 Reinforcement Learning

   Supervised Learning is the field for labeled data for predication and classification them using Regression and it different types, and classify using different ML Algorithm like (SVM, RF etc...). Unsupervised Learning is the field for unlabeled data for predication and clustering them using  different types of clustering, Algorithm like (SVM, RF etc...), whereas in Reinforcement learning the ability of learning is going to move ahead here we train out machine using plenty to avoid mistake again by using these technique machine able to work smart than before.

   The journey of Machine learning shows it is the collection statistical model base algorithm to make you machine smart in term of prediction and analysis. ML is not a new technology, first introduced in 1950 till now a lot of modern algorithms make their place in ML domain. ML used in different domains as well like Fraud Detection, Data Analysis, and many more.


Data Mining:
  Data mining (DM), is the process of finding/Discovering the designing pattern from large amount of data set by using different algorithm including the machine learning, statistical and database, therefore it is also called knowledge discovery in databases (KDD).

  In simple word, in this process we are finding those data set which is invisible but inherited from actual data set that is accurate and useful for us after discovering.It is an iterative process of creating a predictive and descriptive model, by uncovering previously unknown trends and pattern in vast amounts of data in order to support decision making. Also, DM applied in the limited area than machine learning because its domain big. Quite often, the data set in Data Mining is massive, complicated, and/or may have special problems (such as there are more variables than observations).

  Now it is time to compare them in term of working, performance and importance':


1.  It is used for extracting knowledge/information and describing about pattern on it from a big amount of data WHEREAS it is used to predict discrete/continuous value using different statistical and modern algorithm.

2.  The concept of Data Mining introduced in 1930 WHEREAS it is introduced in 1950.

3.  Its origin based on unstructured data/data set WHEREAS it is not necessary only unstructured data will be use.

4.  Generally used to identify the classification and clustering between/among different pattern WHEREAS it is not only used for that purpose also for fraud deduction, spam mail, disease identification etc.

5.  It is based/abstracted from Data warehousing that's why another course named Data mining and data warehousing also offered in BS/MS program of CS, WHEREAS it is based on data/machine.

6.  The scope or domain of Data Mining is not enough than Machine learning WHEREAS its area is vast in term of usage.



Author, Fahad Hussain   MSCS, MCS
Fahad Hussain Tutorial CLICK here.
      Voluntary work as a Computer Scientist, to explore the difficulties as simple words!!!

CSS VS SAAS

Introduction to CSS:

Colors and animations are the dream of web designer to make web pages more attractive and colorful. Almost every designer/developer know about the usage of CSS, means cascading style sheet which is language that add the style of your HTML tag’s contents. It shows the display beauty of web pages. We can use CSS in HTML using Three (03) way internal, external and inline. There are 100’s of properties/ attributes available in CSS like background/foreground color, border, shading, animation etc to make webpage alive on internet.

CSS (Cascading Style Sheet):

CSS is used to define styles for your web pages, including the design, layout and variations in display for different devices and screen sizes. 

The snippet of CSS with HTML in which internal CSS has been applied!

<!DOCTYPE html>

<html>

<head>

<style>

body {

    background-color: red;

}

h1 {

    color: green;

    margin-left: 36px;

}

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

But, what is SAAS (Syntactically Awesome Style Sheets):

Now, these day three primary preprocessor of CSS are in the market, namely SAAS, LESS, AND STYLUS. But in this Article we are going to understand the working differences between CSS and SAAS, so, What is CSS Preprocessor, Actually, in these days of professional working in the webpages using of hexadecimal color name, bracket and related material very critical according to the demand, so the scientist come to ground to do solve this problem in the form of CSS preprocessor, it is a scripting language (like JavaScript) that capability to extends the CSS and then compile it into simple CSS.

CSS VS SAAS:

“.SCSS” and “.SASS” are the two basic syntaxes of CSS also called superset of CSS3. Which means that if I have been working on CSS file using CSS3 actually it also a valid SCSS with the extension of .scss. The other extension derived by Hamls’ Terseness, the purpose of designing of .sass to avoid the usage of bracket and semicolon, it has own indentation of line that shows the block as like python. By using SAAS the developer has the better readability than simple CSS also he/she can use variable features to avoid to remember the hexadecimal number of color name like $yellow: #fce473;  on it CSS rules can be nested within each other.

Same above example convert into SCSS code:

<!DOCTYPE html>

<html>

<head>

<style>

$foregroundcolor: #008000;

$backgroundcolor: #ff0000;

$marginsize:30px;

Body

{

background-color: $backgroundcolor;

}

h1

{

Color: $foregroundcolor;

Margin-left: $marginsize;

}

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

Same above example convert in

to SASS code:

<!DOCTYPE html>

<html>

<head>

<style>

$foregroundcolor:red;

$backgroundcolor:green;

$marginsize:30px;

Body

background-color: $backgroundcolor;

h1

Color: $foregroundcolor;

Margin-left: $marginsize;

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

Advantages over CSS:

After understand about the basic differences between them, we can say that SAAS provides better understanding and readability over CSS but for large data file because if you use it or less data file it become overwhelm for you. It provides learning curve and compatibility, feature of variable and holding the different data types value add on it more advantages over CSS by using SAAS we can nestedthe properties of CSS and easily handle the operator on it, also mixinswhich is custom functions that can accept parameters and will prevent useless repetitions. Overall it the good choice for developer to make attractive and more powerful style sheet in the websites.

CSS VS SAAS

Introduction to CSS:

Colors and animations are the dream of web designer to make web pages more attractive and colorful. Almost every designer/developer know about the usage of CSS, means cascading style sheet which is language that add the style of your HTML tag’s contents. It shows the display beauty of web pages. We can use CSS in HTML using Three (03) way internal, external and inline. There are 100’s of properties/ attributes available in CSS like background/foreground color, border, shading, animation etc to make webpage alive on internet.

CSS (Cascading Style Sheet):

CSS is used to define styles for your web pages, including the design, layout and variations in display for different devices and screen sizes. 

The snippet of CSS with HTML in which internal CSS has been applied!

<!DOCTYPE html>

<html>

<head>

<style>

body {

    background-color: red;

}

h1 {

    color: green;

    margin-left: 36px;

}

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

But, what is SAAS (Syntactically Awesome Style Sheets):

Now, these day three primary preprocessor of CSS are in the market, namely SAAS, LESS, AND STYLUS. But in this Article we are going to understand the working differences between CSS and SAAS, so, What is CSS Preprocessor, Actually, in these days of professional working in the webpages using of hexadecimal color name, bracket and related material very critical according to the demand, so the scientist come to ground to do solve this problem in the form of CSS preprocessor, it is a scripting language (like JavaScript) that capability to extends the CSS and then compile it into simple CSS.

CSS VS SAAS:

“.SCSS” and “.SASS” are the two basic syntaxes of CSS also called superset of CSS3. Which means that if I have been working on CSS file using CSS3 actually it also a valid SCSS with the extension of .scss. The other extension derived by Hamls’ Terseness, the purpose of designing of .sass to avoid the usage of bracket and semicolon, it has own indentation of line that shows the block as like python. By using SAAS the developer has the better readability than simple CSS also he/she can use variable features to avoid to remember the hexadecimal number of color name like $yellow: #fce473;  on it CSS rules can be nested within each other.

Same above example convert into SCSS code:

<!DOCTYPE html>

<html>

<head>

<style>

$foregroundcolor: #008000;

$backgroundcolor: #ff0000;

$marginsize:30px;

Body

{

background-color: $backgroundcolor;

}

h1

{

Color: $foregroundcolor;

Margin-left: $marginsize;

}

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

Same above example convert in

to SASS code:

<!DOCTYPE html>

<html>

<head>

<style>

$foregroundcolor:red;

$backgroundcolor:green;

$marginsize:30px;

Body

background-color: $backgroundcolor;

h1

Color: $foregroundcolor;

Margin-left: $marginsize;

</style>

</head>

<body>

<h1>Fahad Hussain Free Computer Education</h1>

<p>fahadhussaincs.blogspot.com</p>

</body>

</html>

Advantages over CSS:

After understand about the basic differences between them, we can say that SAAS provides better understanding and readability over CSS but for large data file because if you use it or less data file it become overwhelm for you. It provides learning curve and compatibility, feature of variable and holding the different data types value add on it more advantages over CSS by using SAAS we can nested the properties of CSS and easily handle the operator on it, also mixins which is custom functions that can accept parameters and will prevent useless repetitions. Overall it the good choice for developer to make attractive and more powerful style sheet in the websites.

XML VS JSON

Overview:

                Storage of data, retrieving, sending and handling of it, going to become a big challenge of these days. We need to understand first which storage platform is best according to our application performance at worst case as like algorithm.  

What is XML and JSON?

JSON and XML can be used to receive data from a browser and web server, where XML is the acronym of Extensible Markup Language which is human readable text software use for storing and transporting data without depend on hardware. It has W3C Recommendation where you can create xml as like HTML but here you can create tag as you like means tags are not predefine. 

Whereas JSON is the acronym of Javascript Object Notation which is text base, written with JavaScript object notation. When the data in text form and we need to exchange data between browser and a server JSON is good choice, at the working stage we can easily convert any javascript object in JSON, to send to browser and server. JSON is more easily to understand the write than XML.

Purpose of XML and JSON:

                To get understand the different programming languages and APIs about the complex data/information we need XML AND JSON.  For example the syntax of ASP.Net  (C#) language cannot got by PYTHON, to overcome this problem we can use XML AND JSON, which is also called cross language readability. In the web services it is very helpful to transfer and receiving data with parsable form.

XML and JSON are the platform of these related database or Storage area where you can store and retrieve date but not in enough size. Normally it is use in web base application to create file format (common information formats) with different web base or other programming languages such as java, C#.

Here is the Snippet which is showing the text base differences between them.

The above example demonstrate us how easily to write JSON than XML, where you can use 06 data type with easy parsing and get to browser by using STRINGIFY function also using AJAX we can create stunning web services where data sending or receiving.

Datatype of Json are: a string,  a number, an object (JSON object) an array, a Boolean, and null string  whereas there is no data types option in xml  also converting javascript into JSON is So easy instead of XML.

JSON Parsing:

<!DOCTYPE html>

<html>

<body>

<h2>Converting JavaScript into JSOM</h2>

<p id="demo"></p>

<script>

var myvariable = '{"name":"Fahad", "age":25, "city":"New Dehli"}'

var myobj = JSON.parse(txt);

document.getElementById("demo").innerHTML = myobj.name + ", " + myobj.age;

</script>

</body>

</html>

XML Parsing:

<!DOCTYPE html>

<html>

<body>

<p id="myId"></p>

<script>

var myparser, myxmlDoc;

var mytext = "<Root><Parent>" +

"<Name>Eve John</Name>" +

"<FatherName>Adam</FatherName>" +

"<BirthYear>2005</BirthYear>" +

"</Parent></Root>";

myparser = new DOMParser();

myxmlDoc = myparser.parseFromString(mytext,"text/xml");

document.getElementById("myId").innerHTML =

myxmlDoc.getElementsByTagName("Name")[0].childNodes[0].nodeValue;

</script>

</body>

</html>

                As the both example explain the complexity to handle the XML File than JSON, therefore many developers prefer to use JSON than XML.

So here we are going to understand the very basic differences between them in easy words.

Basic Differences between XML VS JSON:

XML	JSON
XML stand for Extensible Markup Language.	JSON stand for Javascript Object Notation
Syntax like HTML.	Syntax like programming language (JavaScript).
Not easy to write than JSOM.	Easy to write than XML.
No capability to store data into variable.	Capability to store data into 6 data types.
There is no Array in XML.	Array with 1 and 2 dimensional.
It is document oriented.	It is object oriented.
XML data is secured.	JSON data is less secure than XML.
XML file are readable as I said but less than JSON.	JSON is more easy to read than XML.
XML display easy to web browser with parsing.	JSON cannot display on browser without parsing.
XML support different data types without variable such as graphic, chart etc.	JSON only support 6 data types values which have been defined.

Similarities:

                 Both XML and JSON do the same job but by in the different solving method. Both support Unicode system, also self-describing data, similarly both are interoperable or language independent so that developer use with different programming languages such JavaScript, C#, python and others. 

XML VS JSON

Overview:

                Storage of data, retrieving, sending and handling of it, going to become a big challenge of these days. We need to understand first which storage platform is best according to our application performance at worst case as like algorithm.  

What is XML and JSON?

JSON and XML can be used to receive data from a browser and web server, where XML is the acronym of Extensible Markup Language which is human readable text software use for storing and transporting data without depend on hardware. It has W3C Recommendation where you can create xml as like HTML but here you can create tag as you like means tags are not predefine. 

Whereas JSON is the acronym of Javascript Object Notation which is text base, written with JavaScript object notation. When the data in text form and we need to exchange data between browser and a server JSON is good choice, at the working stage we can easily convert any javascript object in JSON, to send to browser and server. JSON is more easily to understand the write than XML.

Purpose of XML and JSON:

                To get understand the different programming languages and APIs about the complex data/information we need XML AND JSON.  For example the syntax of ASP.Net  (C#) language cannot got by PYTHON, to overcome this problem we can use XML AND JSON, which is also called cross language readability. In the web services it is very helpful to transfer and receiving data with parsable form.

XML and JSON are the platform of these related database or Storage area where you can store and retrieve date but not in enough size. Normally it is use in web base application to create file format (common information formats) with different web base or other programming languages such as java, C#.

Here is the Snippet which is showing the text base differences between them.

The above example demonstrate us how easily to write JSON than XML, where you can use 06 data type with easy parsing and get to browser by using STRINGIFY function also using AJAX we can create stunning web services where data sending or receiving.

Datatype of Json are: a string,  a number, an object (JSON object) an array, a Boolean, and null string  whereas there is no data types option in xml  also converting javascript into JSON is So easy instead of XML.

JSON Parsing:

<!DOCTYPE html>

<html>

<body>

<h2>Converting JavaScript into JSOM</h2>

<p id="demo"></p>

<script>

var myvariable = '{"name":"Fahad", "age":25, "city":"New Dehli"}'

var myobj = JSON.parse(txt);

document.getElementById("demo").innerHTML = myobj.name + ", " + myobj.age;

</script>

</body>

</html>

XML Parsing:

<!DOCTYPE html>

<html>

<body>

<p id="myId"></p>

<script>

var myparser, myxmlDoc;

var mytext = "<Root><Parent>" +

"<Name>Eve John</Name>" +

"<FatherName>Adam</FatherName>" +

"<BirthYear>2005</BirthYear>" +

"</Parent></Root>";

myparser = new DOMParser();

myxmlDoc = myparser.parseFromString(mytext,"text/xml");

document.getElementById("myId").innerHTML =

myxmlDoc.getElementsByTagName("Name")[0].childNodes[0].nodeValue;

</script>

</body>

</html>

                As the both example explain the complexity to handle the XML File than JSON, therefore many developers prefer to use JSON than XML.

So here we are going to understand the very basic differences between them in easy words.

Basic Differences between XML VS JSON:

XML	JSON
XML stand for Extensible Markup Language.	JSON stand for Javascript Object Notation
Syntax like HTML.	Syntax like programming language (JavaScript).
Not easy to write than JSOM.	Easy to write than XML.
No capability to store data into variable.	Capability to store data into 6 data types.
There is no Array in XML.	Array with 1 and 2 dimensional.
It is document oriented.	It is object oriented.
XML data is secured.	JSON data is less secure than XML.
XML file are readable as I said but less than JSON.	JSON is more easy to read than XML.
XML display easy to web browser with parsing.	JSON cannot display on browser without parsing.
XML support different data types without variable such as graphic, chart etc.	JSON only support 6 data types values which have been defined.

Similarities:

                 Both XML and JSON do the same job but by in the different solving method. Both support Unicode system, also self-describing data, similarly both are interoperable or language independent so that developer use with different programming languages such JavaScript, C#, python and others.