HTML – Tags

HTML – Tags


A browser read absolutely all you write in the HTML document. Tags have three parts as I said before, the opening, closing and content.

As you will learn there are hundreds of HTML tags. Absolutely all the elements that will be displayed by a browser need a tag or two.

HTML Code:

Tags are written in small letters. This is the standard of writing in XHTML, and Dynamic HTML.

Above are some examples of tags in HTML.

HTML Code:
<!--acts as a capsule on the content.-->

	<h2>Title (heading)</h2>


Exceptions – tags that do not require closing tag

There are some tags that do not meet the model shown above.The reason is that in fact these tags do not have content. Due to this fact we will use a modified manner of writing these tags.

The simplest example is “linebreak”


This tag is combining the two tags, opening and closing.This way is more efficient to use. Line break is used to tell the browser that we want to get down a line below, but not closing paragraph.

Following this example, other tags have been modified to be write in a simpler and quicker way.

HTML Code:
<img src="../img/image.jpg" /> -- Image Tag --

<br /> -- Line Break Tag --

<input type="text" size="12" /> -- Input Field --

As you can see the browser is able to reproduce the image as long as we provide the location using the attribute “scr”. More about this in the next tutorial.


Python Example for Beginners

Two Machine Learning Fields

There are two sides to machine learning:

  • Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
  • Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes

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