Earlier I posted about Artificial Intelligence
Today I came with one of its branch to explain it briefly that is Natural Language Processing (NLP)

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What is meant by Natural Language Processing?

(NLP)Natural Language Processing enables machines to understand human language. Its purpose is to create systems that can make sense of the text and automatically perform tasks such as translation, spell checking, or title editing.

It enables computers to understand human language. After the sessions, NLP analyzes sentence structure and meaning for each word, and then uses algorithms to extract the meaning and deliver the results. In other words, it makes sense in human language to be able to perform different tasks automatically.

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Perhaps, the most well-known examples of NLP that work are real helpers, such as Google Assist, Siri and Alexa. The NLP understands written and spoken text such as "we are going to picnic." , convert it into numbers, making it easier for machines to understand.

One of the most popular NLP chat apps. They help support teams solve problems by understanding common language requests and responding automatically.

There are many other daily applications you use, where you may have encountered NLP without paying attention. Text recommendations when composing an email, providing a translation of Facebook posts written in a different language, or filtering unwanted promotional emails in your spam folder.

AI is the umbrella term for machines that mimic human intelligence. AI includes systems that mimic cognitive skills, such as learning from examples and solving problems. This includes many applications, from self-driving cars to forecasting systems.

How does NLP work?

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Natural Language Processing (NLP) works on how computers understand and interpret human language. With NLP, machines can make sense of written or spoken text and perform tasks such as translation, keyword extraction, title editing, and more.

But to make these processes change and deliver accurate answers, you will need machine learning. Machine learning is the process of using algorithms that teach machines how to learn automatically and evolve from experience without explicit programming.

NLP is used by chatbotst interpret what we as user say and what we intend to do, and machine learning to deliver more accurate responses by learning from past interactions.

NLP strategies.

NLP uses different techniques to help computers understand text but here we discuss the two main strategies.

1• Syntactic analysis

2• Semantic analysis

1•Syntactic Analysis

Performance analysis analyzes text using the basic rules of grammar to identify sentence structure, how words are arranged, and how words are related.

Some of its main functions include:

Making tokens consists of dividing the text into smaller parts called tokens (either sentences or words) to make the text easier to grasp.
The speech tag section (PoS tag) labels tokens like action, extension, adjective, noun, etc. This helps to insert the meaning of the word (for example, the word "letter" means different things when used as an action or noun).
Lemmatization & stemming consists of reducing the variables in their form to make them easier to analyze.
Stop-word suspension removes frequent words that do not add any semantic value, like me, they have, love yours, etc.

2• Semantic Analysis

Semantic analysis focuses on finding the meaning of the text. First, study the meaning of each word (lexical semantics). Next, it looks at the combination of words and what they mean in context. The main sub-functions of semantic analysis are:

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The grammatical construction of the Word seeks to determine the context in which a word is used in a particular context.
Relationship extensions try to understand how organizations (places, people, organizations, etc.) relate to the text.

Uses of NLP

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•Understanding the review:

NLP tools help companies understand how their customers see themselves on all social media, whether emails, product reviews, social media posts, surveys, and more.

• Increase efficiency:

Not only can AI tools be used to understand online conversations and how customers talk about businesses, they can be used to perform repetitive and time-consuming tasks, increase efficiency, and let the employees to focus on their tasks.

•Sensory Analysis

Emotional analysis identifies emotions in a text and classifies ideas as positive, negative, or neutral. You can see how it works by attaching text to this free emotional analysis tool.

By analyzing social media posts, product reviews, or online surveys, companies can gain an understanding of how customers feel about products or products. For example, you can analyze tweets about your product in real time and get ideas from angry customers right away.

•Language translation:

Machine translation technology has seen significant improvements over the past few years, with Facebook translation reaching more human performance in 2019.

•Better communication

Translation tools enable businesses to communicate in different languages, to help them improve their global communication or to enter new markets.
You can also train translating tools to understand different terms in any given industry, such as finance or medicine. So you do not have to worry about common misconceptions about standard translation tools.

•Text output

Text extraction enables you to extract pre-defined details in the text. When dealing with large amounts of information, this tool helps you identify and extract relevant keywords and features (such as product codes, colors, and specs), and organizations with names (such as people's names, location.

There is a lot about NLP to explain more because it is a vast topic but couldn't possible to explain here all.
Hope it will be Informative to you. Thanks for your time.
Special thanks to
@cryptokraze
@Suboohi
@siz-official