Noah  Rowe

Noah Rowe

1594674960

NLP- Neuro Linguistic Programming and Spam Detection

Hi my fellow people, “**Rhymes the rhyme” — **The tune for abcdefg song is same as the tune of twinkle twinkle little star!. Here let’s look into the requirements for building up a NLP model.

What is NLP?

Natural Language processing is a branch of AI that helps computers to understand, interpret and manipulate human language.NLP helps developers to organize and structure knowledge to perform tasks like translation, summarization, named entity recognition, relationship extraction, speech recognition, topic segmentation etc.

Components of NLP:

Image for post

  1. Morphological Analysis: Break chunks of language input into sets of token corresponding to paragraphs, sentences and words. Eg: Uneasy to “un” + “easy”.
  2. **Syntax Analysis: **To check that a sentence is well formed or not and to break it up into a structure that shows syntactic relationship between the different words. Eg: The school goes to the boy -Sentence “rejected”.
  3. **Semantic Analysis: **Draws exact meaning or dictionary meaning from the text. It shows how words are associated with each other. Eg: Hot Coffee — accepted as two words extracts to be meaningful.
  4. **Pragmatic analysis: **Fits the actual objects/events which exits in a given context with object reference obtained during semantic phase. It discovers the intent of the text. Eg: “Close the window” -interpreted as request instead of order. Another Eg: “Place the apple in the basket on the shelf” -It has 2 semantic interpretations and pragmatic analyzer will choose between these two possibilities.

#spam-detection #nlp #machine-learning #nltk #data-science #data analysis

What is GEEK

Buddha Community

NLP- Neuro Linguistic Programming and Spam Detection
Noah  Rowe

Noah Rowe

1594674960

NLP- Neuro Linguistic Programming and Spam Detection

Hi my fellow people, “**Rhymes the rhyme” — **The tune for abcdefg song is same as the tune of twinkle twinkle little star!. Here let’s look into the requirements for building up a NLP model.

What is NLP?

Natural Language processing is a branch of AI that helps computers to understand, interpret and manipulate human language.NLP helps developers to organize and structure knowledge to perform tasks like translation, summarization, named entity recognition, relationship extraction, speech recognition, topic segmentation etc.

Components of NLP:

Image for post

  1. Morphological Analysis: Break chunks of language input into sets of token corresponding to paragraphs, sentences and words. Eg: Uneasy to “un” + “easy”.
  2. **Syntax Analysis: **To check that a sentence is well formed or not and to break it up into a structure that shows syntactic relationship between the different words. Eg: The school goes to the boy -Sentence “rejected”.
  3. **Semantic Analysis: **Draws exact meaning or dictionary meaning from the text. It shows how words are associated with each other. Eg: Hot Coffee — accepted as two words extracts to be meaningful.
  4. **Pragmatic analysis: **Fits the actual objects/events which exits in a given context with object reference obtained during semantic phase. It discovers the intent of the text. Eg: “Close the window” -interpreted as request instead of order. Another Eg: “Place the apple in the basket on the shelf” -It has 2 semantic interpretations and pragmatic analyzer will choose between these two possibilities.

#spam-detection #nlp #machine-learning #nltk #data-science #data analysis

8 Open-Source Tools To Start Your NLP Journey

Teaching machines to understand human context can be a daunting task. With the current evolving landscape, Natural Language Processing (NLP) has turned out to be an extraordinary breakthrough with its advancements in semantic and linguistic knowledge. NLP is vastly leveraged by businesses to build customised chatbots and voice assistants using its optical character and speed recognition techniques along with text simplification.

To address the current requirements of NLP, there are many open-source NLP tools, which are free and flexible enough for developers to customise it according to their needs. Not only these tools will help businesses analyse the required information from the unstructured text but also help in dealing with text analysis problems like classification, word ambiguity, sentiment analysis etc.

Here are eight NLP toolkits, in no particular order, that can help any enthusiast start their journey with Natural language Processing.


Also Read: Deep Learning-Based Text Analysis Tools NLP Enthusiasts Can Use To Parse Text

1| Natural Language Toolkit (NLTK)

About: Natural Language Toolkit aka NLTK is an open-source platform primarily used for Python programming which analyses human language. The platform has been trained on more than 50 corpora and lexical resources, including multilingual WordNet. Along with that, NLTK also includes many text processing libraries which can be used for text classification tokenisation, parsing, and semantic reasoning, to name a few. The platform is vastly used by students, linguists, educators as well as researchers to analyse text and make meaning out of it.


#developers corner #learning nlp #natural language processing #natural language processing tools #nlp #nlp career #nlp tools #open source nlp tools #opensource nlp tools

Coding 101: Programming Language Building Blocks

This article will introduce the concepts and topics common to all programming languages, that beginners and experts must know!

Do you want to learn a programming language for the first time?

Do you want to improve as a Programmer?

Well, then you’re in the right place to start. Learn any programming language without difficulty by learning the concepts and topics common to all programming languages.

Let me start by answering the following questions:

  • Why learn Programming?
  • What is Programming?
  • How to Learn a Programming Language?

Why learn Programming❔

Programming develops creative thinking

Programmers solve a problem by breaking it down into workable pieces to understand it better. When you start learning to program, you develop the habit of working your way out in a very structured format. You analyze the problem and start thinking logically and this gives rise to more creative solutions you’ve ever given.

Whether you want to uncover the secrets of the universe, or you just want to pursue a career in the 21st century, basic computer programming is an essential skill to learn.

_– _Stephen Hawking

Everybody in this country should learn how to program a computer… because it teaches you how to think.

_- _Steve Jobs

Programming Provides Life-Changing Experiences

Programming always provides you with a new challenge to take risks every time and that teaches you to take risks in your personal life too. The world is filled up with websites, apps, software and when you build these yourself you’ll feel more confident. When a programmer solves a problem that no one has ever solved before it becomes a life-changing experience for them.

What is Programming🤔?

program is a set of instructions to perform a task on a computer.

Programming is the process of designing and building an executable computer program to accomplish a specific task.

Well, according to me programming is like raising a baby. We provide knowledge (data) to help understand a baby what’s happening around. We teach a baby to be disciplined (and much more) by making rules.

Similarly, a computer is like a baby. We set rules and provide data to the computer through executable programs with the help of a Programming Language.

(Photo by Clément H on Unsplash)

That’s it👍. If you can understand this basic concept of programming, you’re good to go. Pick up a programming language and start learning. Read the following section to get an idea of where to start.

My recommendation is to choose Python Programming Language as a start, because it’s beginner-friendly.

#programming #programming-tips #programming-language #programming-top-story #computer-science #data-structures-and-algorithms #tips-for-programmers #coding

Kolby  Wyman

Kolby Wyman

1596726420

Why NLP Suffers From The Issue Of Underrepresented Languages

Natural language processing (NLP) has made several remarkable breakthroughs in recent years by providing implementations for a range of applications including optical character recognition, speech recognition, text simplification, question-answering, machine translation, dialogue systems and much more.

With the help of NLP, systems learn to identify spam emails, suggest medical articles or diagnosis related to a patient’s symptoms, etc. NLP has also been utilised as a critical ingredient in case of crucial decision-making systems such as criminal justice, credit, allocation of public resources, sorting a list of job candidates, to name a few.

However, despite all these critical use cases, NLP is still lagging and faces the problem of underrepresentation. For instance, one of the significant limitations of NLP is the ambiguity of words in languages. The ambiguity and imprecise characteristics of the natural languages make NLP difficult for machines to implement.

#developers corner #issues in nlp #natural language processing #nlp ai #nlp papers #nlp research

Programming In Acceleration: Levelling Up Programming Skills

Some require and some are not. But acceleration programs might require you to build one. I’ll tell you how I made a computer program for the competition.

1-Researched the source codes and pasted it on my VS code

Written on the internet “blockchain-based ticket codes” and found the Ethereum source codes in Github. Then, I’ve just copied and pasted on my VS code by naming with .sol extension. Then, I’ve got my hands on the code itself and started to correct the mistakes that the editor has shown so far. Managed to reduce 189 errors to 58 within two hours. The rest was handled by my teammate when I sent the code I’ve edited. He just fixed the codes in three more hours and my mistake was not to increase the gas price. We increased the gas price on the remix and everything worked. And he just tested the software on scalability and security. It was the perfect garment for us that everything worked except the indentation errors.

What should’ve been done by us

Found all the codes including testing, copied them, and pasted them to our text editor for further analysis. Still, we had the prototype and we could write all the test codes, migrations, etc. if needed. Even more, we should’ve researched the codes to our project before using one of the examples.

#acceleration-program #program-analysis #programming #startup #acceleration #data analysis