{"id":189167,"date":"2024-09-18T06:30:00","date_gmt":"2024-09-18T05:30:00","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=189167"},"modified":"2024-09-19T10:07:29","modified_gmt":"2024-09-19T09:07:29","slug":"all-about-nlp","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/all-about-nlp","title":{"rendered":"NLP Explained: Everything to Know About Natural Language Processing in AI"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"189167\" class=\"elementor elementor-189167\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-be9938e e-flex e-con-boxed e-con\" data-id=\"be9938e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2c52291 elementor-widget elementor-widget-heading\" data-id=\"2c52291\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><p class=\"elementor-heading-title elementor-size-default\">Natural Language Processing (NLP) is a branch of artificial intelligence focused on the interaction between computers and humans through natural language. Discover everything about this rapidly expanding field of research!<\/p>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8642ffe elementor-widget elementor-widget-text-editor\" data-id=\"8642ffe\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><span style=\"font-weight: 400;\">In the past, to <\/span><b>interact with computers<\/b><span style=\"font-weight: 400;\">, we mainly used the keyboard and mouse. However, thanks to <a href=\"https:\/\/datascientest.com\/en\/artificial-intelligence-definition\">AI<\/a>, machines can now <\/span><b>understand, interpret, and respond intelligently to commands and texts<\/b><span style=\"font-weight: 400;\"> provided by human users.<\/span><\/p><p><span style=\"font-weight: 400;\">This feat is attributed to a technology called NLP: Natural Language Processing. With the rise of <\/span><b>virtual assistants<\/b><span style=\"font-weight: 400;\">, <\/span><b>automatic translation systems<\/b><span style=\"font-weight: 400;\">, <\/span><b>chatbots<\/b><span style=\"font-weight: 400;\">, and many other applications, it is now in the spotlight!<\/span><\/p><p><span style=\"font-weight: 400;\">Its history began with the first automatic translation tools that emerged in the 1950s, but it is only with advancements in Machine Learning and data processing that major progress has been made, driving many technological innovations&#8230;<\/span><\/p><p><span style=\"font-weight: 400;\">So, what is NLP, what are its fundamentals, what <\/span><b>algorithms<\/b><span style=\"font-weight: 400;\"> are behind its functioning, and what are its applications? This is what you will discover in the rest of this article!<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5341ed7 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"5341ed7\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">All about NLP systems<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f91dca9 e-flex e-con-boxed e-con\" data-id=\"f91dca9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2dbf010 elementor-widget elementor-widget-heading\" data-id=\"2dbf010\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Data Analysis to Uncover the Secrets of Language<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2e869fa elementor-widget elementor-widget-text-editor\" data-id=\"2e869fa\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Complex and multifaceted, <\/span><b>natural language<\/b><span style=\"font-weight: 400;\"> consists of several concepts that must be understood and analyzed to enable automated processing.<\/span><\/p><p><b>Syntax<\/b><span style=\"font-weight: 400;\"> concerns the structure of sentences and the rules governing the organization of words. It allows determining if a sentence is grammatically correct and identifying the relationships between its different elements.<\/span><\/p><p><span style=\"font-weight: 400;\">On the other hand, <\/span><b>semantics<\/b><span style=\"font-weight: 400;\"> deals with the meaning of words and sentences. It is essential for understanding the meaning of texts and performing tasks such as lexical disambiguation and information extraction.<\/span><\/p><p><span style=\"font-weight: 400;\">Another notion is <\/span><b>pragmatics<\/b><span style=\"font-weight: 400;\">, which focuses on the use of language in context and on how contexts influence the interpretation of meaning.<\/span><\/p><p><span style=\"font-weight: 400;\">Simply put, it is indispensable for understanding the intentions behind sentences and for managing aspects like <\/span><b>irony and humor<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><b>Morphology<\/b><span style=\"font-weight: 400;\">, on the other hand, is the study of the structure of words and their variations. It includes the analysis of prefixes, suffixes, roots, and inflections.<\/span><\/p><p><span style=\"font-weight: 400;\">Finally, <\/span><b>phonology<\/b><span style=\"font-weight: 400;\"> concerns the sounds of language and their organization. It is more relevant for voice recognition and synthesis systems.<\/span><\/p><p><span style=\"font-weight: 400;\">Thus, <\/span><b>NLP encompasses a variety of tasks<\/b><span style=\"font-weight: 400;\">, each aiming to solve specific aspects of language understanding and generation.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4fc42ef elementor-widget elementor-widget-image\" data-id=\"4fc42ef\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"457\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_1.jpg\" class=\"attachment-full size-full wp-image-189170\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_1.jpg 800w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_1-300x171.jpg 300w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_1-768x439.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8166d81 elementor-widget elementor-widget-text-editor\" data-id=\"8166d81\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>Lexical analysis<\/b><span style=\"font-weight: 400;\"> involves segmenting text into smaller units, such as words and tokens, and identifying their morphological properties.<\/span><\/p><p><span style=\"font-weight: 400;\">Conversely, to determine the <\/span><b>grammatical structure<\/b><span style=\"font-weight: 400;\"> of sentences, <\/span><b>syntactic analysis<\/b><span style=\"font-weight: 400;\"> is used, allowing the construction of trees or syntactic dependencies.<\/span><\/p><p><span style=\"font-weight: 400;\">A <\/span><b>semantic analysis<\/b><span style=\"font-weight: 400;\"> aims to understand the meaning of words and sentences, particularly through word disambiguation and interpreting semantic relationships.<\/span><\/p><p><span style=\"font-weight: 400;\">Beyond analysis, NLP enables text generation: <\/span><b>creating coherent and meaningful sentences and texts<\/b><span style=\"font-weight: 400;\"> from structured data or other forms of internal representation.<\/span><\/p><p><span style=\"font-weight: 400;\">It also allows for automatic translation, i.e., the <\/span><b>conversion of texts from one language to another<\/b><span style=\"font-weight: 400;\"> while maintaining the meaning and style as faithfully as possible.<\/span><\/p><p><span style=\"font-weight: 400;\">It can also be used to summarize a long text by condensing it into a shorter version while preserving essential information and the overall meaning.<\/span><\/p><p><span style=\"font-weight: 400;\">These different tasks form the foundation of NLP, on which advanced techniques and practical applications rest, which we will discuss next.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e036d46 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"e036d46\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-analyst-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Become a Data Analyst<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c3e2052 e-flex e-con-boxed e-con\" data-id=\"c3e2052\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-51caa84 elementor-widget elementor-widget-heading\" data-id=\"51caa84\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">NLP Techniques and Algorithms<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f97cb7b elementor-widget elementor-widget-text-editor\" data-id=\"f97cb7b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Statistical models and <a href=\"https:\/\/datascientest.com\/en\/boosting-business-with-3-essential-machine-learning-algorithms\">Machine Learning algorithms<\/a> are the beating heart of modern NLP. They enable machines to learn patterns in <\/span><b>textual data<\/b><span style=\"font-weight: 400;\"> and perform various <\/span><b>language processing tasks<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">For example, classification and regression algorithms are used for tasks like part-of-speech tagging, sentiment analysis, and text classification.<\/span><\/p><p><span style=\"font-weight: 400;\">Some of the most commonly used include <\/span><a href=\"https:\/\/datascientest.com\/en\/svm-support-vector-machines-unveiled-understanding-implementation-significance\"><span style=\"font-weight: 400;\">support vector machines (SVM)<\/span><\/a><span style=\"font-weight: 400;\">, <strong>random forests<\/strong>, and <strong>logistic regressions<\/strong>.<\/span><\/p><p><span style=\"font-weight: 400;\">In parallel, language models such as n-grams, <a href=\"https:\/\/datascientest.com\/en\/markov-models-get-ready\">hidden Markov models (HMM)<\/a>, and <a href=\"https:\/\/datascientest.com\/en\/bayesian-optimization-definition-and-operation\">Bayesian models<\/a> are used to predict the <\/span><b>probability of word sequences<\/b><span style=\"font-weight: 400;\">: a crucial process for voice recognition, spell checking, and text generation.<\/span><\/p><p><span style=\"font-weight: 400;\">Before the era of Machine Learning, however, NLP systems were mainly <\/span><b>rule-based<\/b><span style=\"font-weight: 400;\">. These approaches are less common today but remain useful in certain contexts.<\/span><\/p><p><span style=\"font-weight: 400;\">Rule-based systems use sets of <\/span><b>manually encoded grammatical rules<\/b><span style=\"font-weight: 400;\"> to analyze and generate language. These include context-free grammars and finite state machines.<\/span><\/p><p><span style=\"font-weight: 400;\">More recently, <a href=\"https:\/\/datascientest.com\/en\/all-about-artificial-intelligence-and-finance-sector\">advances in Deep Learning<\/a> have revolutionized NLP. They allow for far superior performance compared to traditional methods.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-17e0ffe elementor-widget elementor-widget-image\" data-id=\"17e0ffe\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"457\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_2.jpg\" class=\"attachment-full size-full wp-image-189171\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_2.jpg 800w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_2-300x171.jpg 300w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_2-768x439.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f036f1e elementor-widget elementor-widget-text-editor\" data-id=\"f036f1e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/datascientest.com\/en\/recurrent-neural-network-what-is-it\">RNN (recurrent neural networks)<\/a>, especially LSTM (Long Short-Term Memory) and <\/span><b>GRU (Gated Recurrent Units)<\/b><span style=\"font-weight: 400;\">, are used for sequential tasks like translation and text generation.<\/span><\/p><p><span style=\"font-weight: 400;\">Similarly, <a href=\"https:\/\/datascientest.com\/en\/convolutional-neural-network-everything-you-need-to-know\">CNN (convolutional neural networks)<\/a> were initially developed <\/span><b>for computer vision<\/b><span style=\"font-weight: 400;\"> but have also been applied to NLP for tasks like sentiment analysis.<\/span><\/p><p><span style=\"font-weight: 400;\"><a href=\"https:\/\/datascientest.com\/en\/empowering-natural-language-processing-with-hugging-face-transformers-api\">Transformer-based models<\/a>, such as <strong>BERT<\/strong> and <a href=\"https:\/\/datascientest.com\/en\/all-about-generated-pre-trained-transformers\">GPT<\/a>, have also significantly improved NLP capabilities. They allow better understanding of context through <\/span><b>bidirectional attention<\/b><span style=\"font-weight: 400;\"> and are at the forefront of the latest advances.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-38d6399 e-flex e-con-boxed e-con\" data-id=\"38d6399\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-700a2d2 elementor-widget elementor-widget-heading\" data-id=\"700a2d2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What Is It Used For? What Are the Applications?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ace3d9b elementor-widget elementor-widget-text-editor\" data-id=\"ace3d9b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">One of the key applications of NLP is sentiment analysis. It involves <\/span><b>detecting emotions<\/b><span style=\"font-weight: 400;\"> expressed in a text.<\/span><\/p><p><span style=\"font-weight: 400;\">This is a very common practice in marketing, online reputation management, and consumer review studies.<\/span><\/p><p><span style=\"font-weight: 400;\">Using classification algorithms and neural networks, <\/span><b>NLP systems<\/b><span style=\"font-weight: 400;\"> can identify positive, negative, or neutral sentiments in product reviews, social media comments, or news articles.<\/span><\/p><p><span style=\"font-weight: 400;\">This allows companies to monitor public opinions, adapt their marketing strategies, and respond to customer needs.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-333cdf2 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"333cdf2\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/deep-learning-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Follow a course in Deep Learning<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73fe797 elementor-widget elementor-widget-text-editor\" data-id=\"73fe797\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Beyond social media and other customer feedback, <\/span><b>NLP technologies<\/b><span style=\"font-weight: 400;\"> are very useful for extracting and searching for relevant information in vast sets of textual data.<\/span><\/p><p><span style=\"font-weight: 400;\">Search engines like Google use such algorithms to understand user queries and provide the most relevant results. The entire functioning of the internet relies on this system.<\/span><\/p><p><span style=\"font-weight: 400;\">Moreover, <\/span><b>virtual assistants<\/b><span style=\"font-weight: 400;\"> like Siri, Alexa, or Google Assistant also rely on NLP. They use speech recognition technologies, natural language understanding, and response generation to interact with users smoothly and naturally.<\/span><\/p><p><span style=\"font-weight: 400;\">The same technology is employed for <\/span><b>chatbots<\/b><span style=\"font-weight: 400;\">, especially those automating customer service by providing instant answers to common questions. They help solve problems and thus speed up company operations.<\/span><\/p><p><span style=\"font-weight: 400;\">However, the most well-known and widespread application of NLP is probably<\/span><b> automatic translation<\/b><span style=\"font-weight: 400;\">. From the first rule-based systems to the latest generation neural translation models, considerable progress has been made.<\/span><\/p><p><span style=\"font-weight: 400;\">Among the most popular tools in this field are <\/span><b>Google Translate<\/b><span style=\"font-weight: 400;\"> or <\/span><b>DeepL<\/b><span style=\"font-weight: 400;\">. They use <a href=\"https:\/\/datascientest.com\/en\/deep-neural-network-what-is-it-and-how-is-it-working\">deep neural networks<\/a> to produce translations that are as accurate as they are natural.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-13246b0 elementor-widget elementor-widget-image\" data-id=\"13246b0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"457\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_3.jpg\" class=\"attachment-full size-full wp-image-189175\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_3.jpg 800w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_3-300x171.jpg 300w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_3-768x439.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7e37dd1 e-flex e-con-boxed e-con\" data-id=\"7e37dd1\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-21712d3 elementor-widget elementor-widget-heading\" data-id=\"21712d3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">The Ambiguity of Natural Language: An Obstacle to Overcome<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5fc4e19 elementor-widget elementor-widget-text-editor\" data-id=\"5fc4e19\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">One of the main challenges of NLP is to <\/span><b>handle the inherent ambiguity and complexity of human language<\/b><span style=\"font-weight: 400;\">. Words can have multiple meanings, and sentences can be interpreted in different ways depending on their structure.<\/span><\/p><p><span style=\"font-weight: 400;\">For example, in English, the word \u201cBark\u201d can refer to the outer layer of a tree or a dog&#8217;s sound. NLP systems, therefore, need to <\/span><b>disambiguate<\/b><span style=\"font-weight: 400;\"> these terms correctly based on the context.<\/span><\/p><p><span style=\"font-weight: 400;\">The meaning of words and sentences can also change depending on <\/span><b>context and culture<\/b><span style=\"font-weight: 400;\">. Idioms, idiomatic expressions, and cultural references pose additional challenges.<\/span><\/p><p><span style=\"font-weight: 400;\">For example, the expression \u201ckick the bucket\u201d means \u201cto die\u201d in colloquial English, but its literal translation would be incomprehensible in another language without <\/span><b>cultural knowledge<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Another problem is that NLP models can reflect and amplify biases present in the data on which they are trained, raising <\/span><b>ethical concerns<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">The textual data used for training can indeed contain cultural, social, and gender biases.<\/span><\/p><p><span style=\"font-weight: 400;\">For example, if a model is primarily trained on texts in English from American sources, it might not <\/span><b>understand or represent the cultures and dialects of other regions well<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b4b5ee2 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"b4b5ee2\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Become a Machine Learning Engineer<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1d7ad36 elementor-widget elementor-widget-text-editor\" data-id=\"1d7ad36\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Similarly, NLP systems can perpetuate <\/span><b>stereotypes<\/b><span style=\"font-weight: 400;\"> and <\/span><b>discrimination<\/b><span style=\"font-weight: 400;\">. Therefore, methods need to be developed to identify and mitigate these biases to <\/span><b>create fair and responsible systems<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">On a large scale, natural language processing can also pose challenges in terms of <\/span><b>computing resources<\/b><span style=\"font-weight: 400;\"> and <\/span><b>processing time<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Analyzing and understanding large amounts of textual data requires enormous computing power. Only the optimization of models allows their functioning without sacrificing precision.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5fca152 e-flex e-con-boxed e-con\" data-id=\"5fca152\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7c1fc7d elementor-widget elementor-widget-heading\" data-id=\"7c1fc7d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusion: NLP, a Revolution for Human-Machine Interactions<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f393956 elementor-widget elementor-widget-text-editor\" data-id=\"f393956\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In the future, the field of NLP will continue to develop thanks to the emergence of new technologies. Future generative language models like <\/span><b>GPT-5<\/b><span style=\"font-weight: 400;\"> and <\/span><b>multimodal models<\/b><span style=\"font-weight: 400;\">, integrating text or image, will continue to push the limits.<\/span><\/p><p><span style=\"font-weight: 400;\">The same goes for <\/span><b>transfer learning techniques<\/b><span style=\"font-weight: 400;\">. Furthermore, NLP is increasingly integrated with other AI fields like computer vision and <a href=\"https:\/\/datascientest.com\/en\/all-about-internet-of-things\">the Internet of Things<\/a>.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b188254 elementor-widget elementor-widget-image\" data-id=\"b188254\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"457\" src=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_4.jpg\" class=\"attachment-full size-full wp-image-189188\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_4.jpg 800w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_4-300x171.jpg 300w, https:\/\/datascientest.com\/en\/files\/2024\/09\/Natural_Language_Processing_DataScientest_4-768x439.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1565415 elementor-widget elementor-widget-text-editor\" data-id=\"1565415\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Many industries like <\/span><b>customer service<\/b><span style=\"font-weight: 400;\">, <\/span><b>marketing<\/b><span style=\"font-weight: 400;\">, and <\/span><b>education<\/b><span style=\"font-weight: 400;\"> will likely be profoundly transformed.<\/span><\/p><p><span style=\"font-weight: 400;\">To <\/span><b>become an expert in NLP<\/b><span style=\"font-weight: 400;\"> or other branches of artificial intelligence, you can turn to <\/span><b>DataScientest<\/b><span style=\"font-weight: 400;\">. Our organization offers several AI-focused training programs that will provide you with extensive knowledge.<\/span><\/p><p><span style=\"font-weight: 400;\">You can choose between <a href=\"https:\/\/datascientest.com\/en\/deep-learning-course\">our Deep Learning courses<\/a>, <a href=\"https:\/\/datascientest.com\/en\/ml-ops-course\">MLOps<\/a>, <a href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">Machine Learning Engineer<\/a>, or <a href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">Data Scientist<\/a>.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-26c2eff elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"26c2eff\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Train with DataScientest<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-37ee850 elementor-widget elementor-widget-text-editor\" data-id=\"37ee850\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">You know everything about NLP. For more information on the same topic, check out <a href=\"https:\/\/datascientest.com\/en\/natural-language-processing-definition-and-principles\">our complete article on NLP<\/a> and <a href=\"https:\/\/datascientest.com\/en\/all-about-deep-learning\">our article on Deep Learning<\/a>!<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6d24d2a e-flex e-con-boxed e-con\" data-id=\"6d24d2a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b27a38a elementor-widget elementor-widget-html\" data-id=\"b27a38a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is Natural Language Processing (NLP)?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"NLP is a branch of artificial intelligence that aims to enable computers to understand, interpret, and generate human language. It combines techniques from linguistics and computer science to analyze and manipulate text or speech.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What are common applications of NLP?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Common applications of NLP include chatbots, machine translation, sentiment analysis, speech recognition, automated text generation, and information extraction from documents.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"How does NLP work?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"NLP works by using algorithms and machine learning models to analyze linguistic structures. 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In the past, to interact with computers, we mainly used the keyboard and mouse. However, thanks to AI, machines can now understand, interpret, and respond [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":189169,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2427],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>NLP Explained: Everything to Know About Natural Language Processing in AI<\/title>\n<meta name=\"description\" content=\"Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and human languages. 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