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Introduction: HTML is a standard markup language for creating Web pages. HTML stands for Hyper Text Markup Language HTML describes the structure of a Web page HTML consists of a series of elements HTML elements tell the browser how to display the content HTML elements are represented by tags HTML tags label pieces of content such as "heading", "paragraph", "table", and so on Note: - Browsers do not display the HTML tags, but use them to make the content of the page. Example: Example Explained The element is the root element of an HTML page The element contains meta information about the document The This is a heading This is a paragraph. This is another paragraph. Note: - Only the content inside the section is displayed in browser. HTML Versions HTML was introduced in the year 1991 by Tim Berners-Lee. Since then there have been many versions of HTML: Version Year HTML 1991 HTML 2.0 1995 HTML 3.2 1997 HTML 4.01 1999 XHTML 2000 HTML5 2014 HTML Editors Web pages are usually created and modified by using professional HTML editors like NetBeans, Notepad++, Visual Studio Code, etc. However, for learning purpose simple text editor like Notepad, TextEdit is recommended. Following steps are too followed to create a web page with Notepad. Step 1: Open Notepad Windows 8 or later: Open the Start Screen (the window symbol at the bottom left on your screen). Type Notepad. Windows 7 or earlier: Open Start > Programs > Accessories > Notepad Step 2: Write Some HTML Code Heading This is my first paragraph. Write or copy some HTML into Notepad. Step 3: Save the HTML Page Save the file on your computer. Select File > Save as in the Notepad menu. Name the file "demo1.htm" and set the encoding to UTF-8 (which is the preferred encoding for HTML files). Step 4: View the HTML Page in Your Browser Open the saved HTML file in your favourite browser (double click on the file, or right-click - and choose "Open with"). Example: HTML Documents All html documents start with a document type declaration: . The HTML document begins with and ends with . The visible part of the HTML document is between and . Example: HTML Headings HTML defines six levels of headings. HTML headings are defined with the to tags. defines the most important heading and defines the least important heading. Example: HTML Paragraphs HTML paragraphs are defined with the tag: Example: HTML Links A link is a connection from one web source to another. Links are specified in HTML using the “a” tag. Syntax: Text to be Displayed href: The href attribute is used to specify the destination address of the link used. Attributes are used to provide additional information about HTML elements. Text to be displayed: It is the visible part of the link. Example: HTML Images HTML images are defined with the tag. Syntax: The alt attribute provides alternative text for users who are unable to view the image. Height and width attributes is used to provide dimensions for the image. Example: HTML Buttons The button tag in HTML is used to define the clickable button. It is usually used to submit the content. The image and text content can be used inside tag. Syntax: Example: HTML Lists A list is a record of short pieces of information. In HTML there are three ways to specify lists of information. All lists must have at least one or more list elements. Types of lists used in HTML are: ul: An unordered list. This will list items using plain bullets. ol: An ordered list. This will use different schemes of numbers to list the items. dl: A definition list. This arranges the items in the same way as they are arranged in a dictionary. Example: HTML Elements HTML element is the collection of start and end tag with the content inserted in between them. In HTML end tag of element is necessary. Otherwise the displayed content may not be displayed correctly. Note: - A HTML element with no content are called empty elements. Empty elements do not have an end tag, such as element (which indicates a line break). Start Tag Element Content End Tag Heading Paragraph -- -- Nested HTML Elements The elements of HTML can be nested. When a HTML element is used inside another HTML element it is called Nested HTML Elements. All HTML documents consists of nested HTML elements. Example: Note: - Some HTML elements will display correctly, even if we forget the end tag like paragraph tag. Empty HTML Elements The element which has no content are called empty elements. is an empty element. Empty elements do not have closing tag. The tag is used for line break. Example: Note: - HTML5 do not require empty elements to be closed, but it is recommended to close all HTML elements properly for reliability. HTML is Not Case Sensitive HTML tags are not case sensitive. In HTML is same as . HTML5 standard do not require lowercase tags, but W3C recommends lowercase in HTML, for stricter document types like XHTML. HTML Attributes An attribute is used to provide extra or additional information about an element. It takes two parameters: a name and a value. Attributes are always specified in the start tag. The value of an attribute must be written within quotes. The href Attribute HTML links are defined with the tag. The link address is specified in the href attribute. Example: The src Attribute HTML images are defined with the tag. The src attribute is used to specify the URL of the source image. Example: The width and height Attribute HTML images uses width and height attributes. It specifies the width and height of the image. Example: The alt Attribute In HTML the alt attribute is used to specify the alternative text to be used, if an image cannot be displayed. The value of alt attribute can be read by screen readers. It can also be heard if someone is listening to the web page. Example: The style Attribute Styles in HTML are basically the rules that describe how a document is presented in a browser. The style attribute is used for styling the element, like color, font, size, etc. Example: The lang Attribute The language attribute contains single value language code which is used to specify the language of the content. The language of a document is declared in the tag. The language is declared with the lang attribute. ... The title Attribute The title attribute is used to specify extra information about the element. When we move cursor over the element then it shows the information. A title attribute is added to the element. Example: Are attributes case sensitive? HTML5 is not case sensitive, i.e. it can be written in either uppercase or lowercase. For example, the title attribute can be written like title or TITLE. But W3C recommends HTML attributes to be in lower case, as demanded for stricter document types like XHTML. HTML Headings HTML has six levels of headings element. The six heading elements are H1, H2, H3, H4, H5 and H6. Importance: Search Engines use headings for indexing the structure and content of the webpage. Headings are used for highlighting important topics. They provide valuable information and tell us about the structure of the document. Note: - HTML headings are used only for headings. It can’t be used for making text BIG or bold. Headings Size Each HTML heading has a default size. Also, size of the headings can be specified with the style attribute using the CSS font-size property. Example: HTML Horizontal Rules The tag in HTML stands for horizontal rule. It is used to insert a horizontal rule or a thematic break in an HTML page to divide or separate document sections. The tag is an empty tag and it does not require an end tag. Example: HTML Element The element is a container for metadata. HTML metadata is data about the HTML document. Metadata is not displayed. The element is always placed in between tag and tag. Example: Note: - Metadata typically define the document title, character set, styles, scripts, and other meta information. HTML Source Code View HTML Source Code To view an HTML Source Code, right-click in an HTML page and select "View Page Source" (in Chrome), or similar in other browsers. This will open a window containing the HTML source code of the page. Inspect HTML Source Code To inspect an HTML Source Code, right-click on an element (or a blank area), and choose "Inspect" or "Inspect Element" to see what elements are made up of. (both the HTML and the CSS can be seen). We can also edit the HTML or CSS on-the-fly in the Elements or Styles panel that opens. HTML Paragraphs The tag in HTML defines a paragraph. It has both opening and closing tag. Things within and is treated as a paragraph. Usually browsers read a line as a paragraph even if the closing tag i.e, is not used. Example: Note: - Browsers automatically add some white space (a margin) before and after a paragraph. HTML Display You cannot be sure how HTML will be displayed. Large or small screens, and resized windows will create different results. With HTML, you cannot change the output by adding extra spaces or extra lines in your HTML code. Example: Note: - The browser removes any extra spaces and extra lines when the page is displayed. HTML Line Breaks The element defines a line break in HTML. tag is used when there is a need of line break ( a new line) without starting a new paragraph. Example: HTML Element The HTML element defines preformatted text. The text inside a element is displayed in a fixed-width font (usually Courier), and it preserves both spaces and line breaks. Example: HTML Styles Styles in HTML are basically rules that describe how a document will be presented in a browser. Style information can be either attached as a separate document or embedded in the HTML document. Example: HTML Style Attribute Setting the style of an HTML element, can be done with the style attribute. Syntax: Background Color The CSS background-color property defines the background color for an HTML element. Example: Text Color The CSS color property defines the text color for an HTML element. Example: Fonts The CSS font-family property defines the font to be used for an HTML element. Example: Text Size The CSS font-size property defines the text size for an HTML element. Example: Text Alignment The CSS text-align property defines the horizontal text alignment for an HTML element Example: HTML Formatting HTML provides us with the ability for formatting text just like we do it in MS Word or any text editing software. Example: HTML Formatting Elements Formatting elements were designed to display special types of text: - Bold text - Important text - Italic text - Emphasized text - Marked text - Small text - Deleted text - Inserted text - Subscript text - Superscript text HTML and Elements The HTML elements defines bold text, without any extra importance. The HTML element defines strong text, with added semantic “strong” importance. Example: HTML and Elements The HTML elements defines italic text, without any extra importance. The HTML element defines emphasized text, with added semantic importance. Example: HTML Element The HTML elements defines smaller text. Example: HTML Element The HTML elements defines marked/highlighted text. Example: HTML Element The HTML elements defines deleted/removed text. Example: HTML Element The HTML elements defines inserted/added text. Example: HTML Element The HTML elements defines subscripted text. Example: HTML Element The HTML elements defines superscripted text. Example: HTML Quotation and Citation Elements The Quotation elements in HTML are used to insert quoted texts in a web page, that is, portion of texts different from the normal texts in the web page. HTML for Short Quotations The HTML elements defines short text. For Short Quotations browsers usually insert quotation marks around the element. Example: HTML for Quotations The HTML elements defines a section which is quoted from another source. elements are usually indented by browsers. Example: HTML for Abbreviations The element is used to define a text as an acronym or abbreviations. The title attribute can be used to show the full version of the abbreviation/acronym when you move cursor over the element. It has both opening and closing tags. This is useful for browsers and search engines. Example: HTML for Contact Information Using the element, we can define an address in a webpage and the text put inside the address tag will be emphasized. Most browsers will add a line break before and after the element. Example: HTML for Work Title This element is used define a title of a work and emphasizes a text. Browsers usually display elements in italic. Example: HTML for Bi-Directional Override The element is used to define a bidirectional override which means that the text written from right to left or left to right. It is used to over-ride the current text direction. It takes an attribute “rtl” to display the text from right to left. Example: HTML Comments The comment tag is used to insert comments in the HTML code. It is used to help the coder and reader to understand the code. The comment tag is useful during the debugging of codes. Syntax: Note: - Comments are not displayed by the browser, but they help document your HTML source code. Example: HTML Colors Colors are used to make the page more attractive. HTML colors are specified using predefined color names, or RGB, HEX, HSL, RGBA, HSLA values. The comment tag is useful during the debugging of codes. Color Names In HTML, a color is specified by using color names. HTML supports 140 standard color names. Example: Background Color We can set the background color for HTML elements. Example: Text Color We can set the color of text in HTML. Example: Border Color We can set the color of borders in HTML. Example: Color Values In HTML, Colors are specified using RGB values, HEX values, HSL values, RGBA values, and HSLA values. Example: RGB Values RGB values are used to specify a color in HTML. Each parameter (red, green, and blue) defines the intensity of the color between 0 and 255. For red color parameters are set as rgb(255, 0, 0), as red is set to its highest value (255) and others are set to 0. Similarly for green rgb(0, 255, 0) and for blue rgb(0, 0, 255). To display the black, all parameters are set to 0, rgb(0, 0, 0). To display the white, all parameters are set to 255, rgb(255, 255, 255). Example: HEX Values HEX stands for Hexadecimal values. Hexadecimal values are used to specify a color in HTML. #rrggbb, here rr (red), gg (green), bb (blue) are hexadecimal values between 00 and ff (same as decimal 0-255). For example, #00ff00 is displayed as green, because green is set to its highest value (ff) and the others are set to the lowest value (00). Example: HSL Value In HTML, a color can be specified using hue, saturation, and lightness (HSL) in the form: hsl(hue, saturation, lightness) Hue is a degree on the color wheel from 0 to 360. 0 is red, 120 is green, and 240 is blue. Saturation is a percentage value, 0% means a shade of gray, and 100% is the full color. Lightness is also a percentage, 0% is black, 50% is neither light or dark, 100% is white. Example: Saturation Saturation is described as the intensity of a color. 100% is pure color, no shades of gray 50% is 50% gray, but you can still see the color. 0% is completely gray, you can no longer see the color. Example: Lightness The lightness of a color is described as how much light is given to the color, where 0% means no light (black), 50% means 50% light (neither dark nor light) 100% means full lightness (white). Example: RGBA Value RGBA color values are an extension of RGB color values with an alpha channel - which specifies the opacity for a color. An RGBA color value is specified with: rgba(red, green, blue, alpha) The range of alpha parameter is 0.0 (fully transparent) and 1.0 (not transparent at all). Example: HSLA Value HSLA color values are an extension of HSL color values with an alpha channel - which specifies the opacity for a color. An HSLA color value is specified with: hsla(hue, saturation, lightness, alpha) The alpha parameter is a number between 0.0 (fully transparent) and 1.0 (not transparent at all). Example: If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion  you can send mail at contact@codersarts.com. Please write your suggestion in comment section below if you find anything incorrect in this blog post

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Information management system remotely Python code Description of task: A mining company wants Nick Industries to design software, to control its fleet of robot explorers and manage the Robot collected information and employees assigned to that area. At this stage you need to program a micro:bit to control a bit:bot as an prototype robot for the project. Your robot will be programmed using Python and needs to model its operation by moving around the robot table and detecting areas of mineral deposits. The robot should indicate by stopping for 10 seconds and displaying an indication that “minerals” have been found. You also need to code software for the information management system. The Information system must include; A splash Screen A logon screen, with access via a user name and password. For security reasons , users cant create their own user names and passwords A menu screen Code to allow the manager to create user names and passwords. Code to allow the manager to enter and retrieve all employee details; name, address, phone numbers, job role, payrate. Code to allow employees to enter and retrieve data from the robot such as mineral location Code to allow employees access to employee details such as names, position . Code to allow the payroll manager to calculate weekly pay after tax. Need python GUI assignment help or need solution of this project please contact at Codersarts and fast and effective code without plagiarism. Find Unique and professional code quickly, contact at Codersarts official website.

This is part - 5 of this series, before this blog we will already created for blog, if you want to learn this blog then i suggest that you can learn previous blog so that you can easily learn this blog. Here, previous blog link are given below you can directly visit from here: Natural Language Processing In Python : Part - 1 : "Text analysis using NLTK" Natural Language Processing In Python : Part - 2 : "N - grams" Natural Language Processing In Python : Part - 3 : Topic, "Detecting text language" Natural Language Processing In Python : Part - 4 : In this we have complete the topic "language identification" In thi blog we will learn all about basic to advanced concepts of the topic Stemming and Lemmatization. What is Stemming and Lemmatization ? Stemming - It is a process of reducing words to its root form even if the root has no dictionary meaning. For eg: beautiful and beautifully will be stemmed to beauti which has no meaning in English dictionary. In other language we can say converts a word into its stem(root form) by removing the some suffix like : “es”, “ing”, “pre” etc. Lemmatization - It is a process of reducing words into their root form or dictionary. It takes into account the meaning of the word in the sentence. For eg: beautiful and beautifully are lemmatised to beautiful and beautifully respectively without changing the meaning of the words. But, good, better and best are lemmatised to good since all the words have similar meaning. Now we will start this blog: Before start it first we need to install all related libraries which helps to running code properly- Install these libraries : First install nltk library- pip install nltk Then import it using: import nltk Types of Lemmatizers: There are many types of Lemmatizer but here we will works some of them like wordnet: Wordnet Lemmatizer spaCy Lemmatization TextBlob Lemmatizer Pattern Lemmatizer Stanford CoreNLP Lemmatization Gensim Lemmatize TreeTagger If you want learn more about lemmatizer then click here "Wordnet" Lemmatizer with NLTK After this install "wordnet", which is collection of english text, which is available free of cost, it is lexical database for the English language aiming to establish structured semantic relationships between words. nltk.download('wordnet') Now start "Lemmatizing" using this : from nltk.stem import WordNetLemmatizer Jupyter notebook output: If lemmatize a simple sentence then first tokenize it then perform operation. Output on Jupiter notebook: "TextBlob" Lemmatizer First install textblob using pip install textblob It is the powerful NLP package Use Word - for single word, and TextBlob - group of words or sentences Examples: With complete sentences: Stemming Here you can learn it with the help of this example Output: Why is Lemmatization better than Stemming? Stemming algorithm works by cutting the suffix from the word and change the meaning of the word but in lemmatization meaning of word in not changed. Thanks for reading this blog in next blog we will learn next topic - Finding unusual words using python NLP If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion  you can send mail at contact@codersarts.com. Please write your suggestion in comment section below if you find anything incorrect in this blog post

In this blog we will learn some important and most useful topics of linear algebra matrix using "Sumpy" python library with the help of examples: In this we will apply some important topics like join, shap(), transpose of matrix and other. Before start if first we need to import library of it. We are now ready to use the Sympy library features . Now we create a matrix using matrix() function, here we tells with python sumpy library in python using: To do this, we simply type sp.Matrix() Here we will create a matrix that contains two rows: the first one will contain elements 0 and 1 and the second will contain elements 5 and 6. Example: X = sp.Matrix( [ 0,1],[5,6] ] ) X # Show Output: [1 3 2 4] Matrix Features .shape attribute Use to check the size of a matrix. Example 1: print(X.shape) Output: (2, 2) #first number represent number of rows and second represent number of columns Example 2: B = sp.Matrix( [ [1,7,3,5], [2,4,6,10] ] ) print(B.shape) Output: (2, 4) Multiplication of matrix Here we can learn it by using some examples which is given below : Let X is a example of matrix which is given above 3*X Output: [3 9 6 12] Addition of matrix: Let X is a example of matrix which is given above 3+X Output: [4 6 5 7] As per above we can apply all simple mathematical operation in python matrix. Transpose of matrix: Let suppose matrix is given as: X = sp.Matrix([[1,2],[3,4]]) X [1 2 3 4] Now we transpose it by using X.T Output: [1 3 2 4] Find Selected element as per row and column Use this code of line to find element as per your selected row and column. X = [1 3 2 4] print( X[1,1] ) #find first row and first column index element Output: 4 or print( X[1,0] ) #use to find first row and zero index element Output: 2 or X[1,:] #find element of first row and all columns indexes Gaussian Elimination Suppose two equations which is given as 𝑥+𝑦=10 2𝑥−𝑦=14 We can create the matrix representation of this system and then run the rref() (stands for reduced-row echelon form). A = sp.Matrix( [ [1, 1, 10], [2, -1, 14] ]) A Output: [ 1 1 10 2 -1 14 ] A.rref() Output: ([1 0 8 0 1 2], ( 0, 1 )) Selecting row and column of matrix: X = sp.Matrix( [ [1, 2, 3], [4, 5, 6] ]) X Output: [ 1 2 3 4 5 6 ] X.row(1) Output: [ 1 2 3 ] Thanks here we completed some basic parts of linear algebra using sumpy, if you want help in advanced topics like swap numbers of matrix, fill value by any value and how to change matrix format by fill any otelementsmets as per your choice. Other python important blogs which is also useful: Data Science Homework Help - NumPy Learn Top Most Python Topics By Codersarts - Part 1 : Pandas Learn Top Most Python Topics By Codersarts - Part 2 : Pandas Doing Math Assignment Using Python By Codersarts If you need any other help related to Data Science then please contact at codersarts website by clicking here If you have any query then please ask through comments sections, which is given below

This is the part - 3 of our series "Natural Language Processing". In previous blog we learn all about text analysis using NLP. In this blog we will learn Detecting text language, this is third topic of this series so ready to learn with NLP Detecting text language. Before start it first read last parts, part - 1 and part - 2. I suggest that you go through part - 1 and part - 2 before start it which is also more help-full for this NLP Series. What is NLP ? It is the branch of data science that consists of systematic processes for analyzing, understanding, and how to driving information from the text data in a smart and efficient manner. First install libraries which is related to NLP - nltk, numpy, matplotlib.pyplot, tweepy, TwitterSearch, unidecode, langdetect, langid, gensim And then import all of these: Install these all libraries which use in this import nltk # https://www.nltk.org/install.html import numpy # https://www.scipy.org/install.html import matplotlib.pyplot # https://matplotlib.org/downloads.html import tweepy # https://github.com/tweepy/tweepy import TwitterSearch # https://github.com/ckoepp/TwitterSearch import unidecode # https://pypi.python.org/pypi/Unidecode import langdetect # https://pypi.python.org/pypi/langdetect import langid # https://github.com/saffsd/langid.py import gensim List of Topics which we will covers in this series: Text-analysis using NLTK library N-Grams Detecting text language Language identifier Stemming and Lemmatization using Bigrams Finding unusual words part of speech and meaning Name-Gender identifier Classify document into categories Sentiment Analysis Sentiment Analysis with NLTK Work with Twitter streaming and Cleaning Language detection Now let's starts Topics -Detecting text language Detecting text language - work with stop word Step - 1 As per previous parts first need to tokenize text and than process it. Jupyter notebook output: Now importing stopword after installing it - Jupyter notebook output: In the last, here final code with count number of stop words in text file - Jupyter notebook output: Thanks for reading, in next blog we will learn new NLP topic - Language identifier Here we add link of last two parts so you can go through it - Natural Language Processing In Python : Part - 1 Natural Language Processing In Python : Part - 2 Thanks for reading this blog, next part we will covers N-Grams. If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion  you can send mail at contact@codersarts.com or visit Codersarts official website. Please write your suggestion in comment section below if you find anything incorrect in this blog post

This is the part - 2 of our series "Natural Language Processing". In previous blog we learn all about text analysis using NLP. In this blog we will learn N - Grams, this is second topics of this series so ready to learn with NLP N-Grams. Before start it first we will again repeat all about general information which we discuss in part - 1 also. I suggest that you go through part - 1 before start it which is also more help-full for this NLP Series. What is NLP ? It is the branch of data science that consists of systematic processes for analyzing, understanding, and how to driving information from the text data in a smart and efficient manner. First install libraries which is related to NLP - nltk, numpy, matplotlib.pyplot, tweepy, TwitterSearch, unidecode, langdetect, langid, gensim And then import all of these: Install these all libraries which use in this import nltk # https://www.nltk.org/install.html import numpy # https://www.scipy.org/install.html import matplotlib.pyplot # https://matplotlib.org/downloads.html import tweepy # https://github.com/tweepy/tweepy import TwitterSearch # https://github.com/ckoepp/TwitterSearch import unidecode # https://pypi.python.org/pypi/Unidecode import langdetect # https://pypi.python.org/pypi/langdetect import langid # https://github.com/saffsd/langid.py import gensim List of Topics which we will covers in this series: Text-analysis using NLTK library N-Grams Detecting text language Language identifier Stemming and Lemmatization using Bigrams Finding unusual words part of speech and meaning Name-Gender identifier Classify document into categories Sentiment Analysis Sentiment Analysis with NLTK Work with Twitter streaming and Cleaning Language detection Now let's starts Topics -N Grams What is N - Grams ? N - Grams used to text mining, Language detection and natural language processing tasks. It is basically set of word which occurs in fixed widow. It is also used to find title of text. It move one word forward at every time and left one work backside. depends on user selection grams. To understand it in general way, here we will go through this basic theoretical example. Let suppose text is: "He is very lazy boy." If N=2(bigrams) orN=3(trigrams) Then generated bigrams(N=2) is: He is is very very lazy lazy boy Total number of N - grams in text Here formula to find total number of N-grams in text file Total Ngrams = X - ( N- 1 ) #where X is total number of word Use of N - Grams There are many uses of N - Grams. like spelling corrections word breaking and text summarization Here we will start it with advanced level with the help of examples : Step - 1: First tokenize text and removing punctuation Run with jupyter notebook: Step 2: Generating 2 - Grams :Frist import this from nltk.util import ngrams Run with jupyter notebook: If you want to select fixed field then used this line of code: print(generated_2grams[:8]) Step 3: Short n grams as per frequency Run with jupyter notebook: Thanks for reading, part - 2 is finished in next part we will learn "Detecting Text Language" If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion  you can send mail at contact@codersarts.com. Please write your suggestion in comment section below if you find anything incorrect in this blog post

This is the part - 1 of our series "Natural Language Processing". In this blog we will covers all related topics and libraries which is use to work with NLP. Before start it first we will know basic information about NLP. What is NLP ? It is the branch of data science that consists of systematic processes for analyzing, understanding, and how to driving information from the text data in a smart and efficient manner. First install libraries which is related to NLP - nltk, numpy, matplotlib.pyplot, tweepy, TwitterSearch, unidecode, langdetect, langid, gensim And then import all of these: Install these all libraries which use in this import nltk # https://www.nltk.org/install.html import numpy # https://www.scipy.org/install.html import matplotlib.pyplot # https://matplotlib.org/downloads.html import tweepy # https://github.com/tweepy/tweepy import TwitterSearch # https://github.com/ckoepp/TwitterSearch import unidecode # https://pypi.python.org/pypi/Unidecode import langdetect # https://pypi.python.org/pypi/langdetect import langid # https://github.com/saffsd/langid.py import gensim List of Topics which we will covers in this series: Text-analysis using NLTK library N-Grams Detecting text language Language identifier Stemming and Lemmatization using Bigrams Finding unusual words part of speech and meaning Name-Gender identifier Classify document into categories Sentiment Analysis Sentiment Analysis with NLTK Work with Twitter streaming and Cleaning Language detection Now let's starts Topics - Text-analysis using NLTK library Run in jupyter notebook Now we will converts it again tokens to text format: Find word from string: Use concordance() method to find word from string Reading string file: f = open('string.txt','rU') #rU means reading file in universal mode f.read() Then you can analysis this file using ntlk. Count word in string: Find similar word: #Distributional similarity: find other words which appear in the same contexts as the specified word; list most similar words first use similar() t.similar('put sting word here') Plot string word as per repetitions By using dispersion_plot, we will plot the graph What is "corpora" in NLP - It is the large collection of text, here we use nltk library - nltk.corpus to find text. Thanks for reading this blog, next part we will covers N-Grams. If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion  you can send mail at contact@codersarts.com or visit Codersarts official website. Please write your suggestion in comment section below if you find anything incorrect in this blog post

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Coders are those person who write computer program to perform certain task over computer. There are lots of programming language available for computer to write code like C, C++, Java, Python, Kotlin, GO etc. The person who write code in java programming language is called java coders. With the help of Java programming we can build different types of software like Desktop application, Web application, Mobile application, System software, Application software. however you still will be called Java coders but area of expertise may be in desktop, web, or Mobile like this. Can anyone be a java coders? Yes, Why not. In today era of rampanting of IT. Need of coders is growing day by day so you can learn by yourself with Youtube and Google. We'll get tons of websites who teaching java coding. Even you don't need computer science degree to be coders. So start today and send you issue if you have any problem or issue while learning. Our java coders or java expert is helping across the world with high potential. How can i start learning Java ? The very first thing you need is computer it may be desktop or laptop, anything is cool! Second think you need is install one software of java which is Java JDK? it may be some alien type of term but that's okay if you are not of technical background. you will be know with these term very soon. After download the Java JDK , any current version it' fine. install the software by following software instruction. if get confused just click next,next , next, untill see a message say software install successfull !! Now you are ready to shoot Go on google type "Hello world Program in Java" #java #javaProgrammingHelp