If you are fresher looking for a promising career path? Then machine learning is ever waning technology in IT sectors. If you intend to begin your career in the IT sector and are intrigued by a machine learning career, there are plenty of job opportunities. Machine learning is booming with many job opportunities among various IT-based industrial jobs, and it is the second most sought-after IT job. So, choosing the machine learning field will provide a secure future for both freshers and professionals. As machine learning processes are used for multiple purposes, the NLP application allows machines to read, understand, and interpret human language.
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Over the years, the machine learning profession has increased by approximately 75%, and this growth is expected to continue further. Working in machine learning is a well-paying career that will be in demand for decades. Healthcare, education, marketing, retail and eCommerce, and financial services are the main sectors already utilizing AI and machine learning. In this blog, we shall discuss the NLP application and what is natural language processing?
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What is Natural Language Processing?
Artificial intelligence's natural language processing component focuses on teaching computers how to understand the human language in all its complexity. This is necessary for machines to comprehend and interpret human speech and ultimately comprehend human communication completely. Computational linguistics, artificial intelligence, and human-computer interaction are just a few of the numerous disciplines that make up natural language processing. To comprehend human language, NLP employs various techniques, including machine learning and statistical methods. These entail dissecting human language into its constituent parts to understand how the aspects relate to one another and cooperate to produce meaning in sentences.
According to the survey, it is stated that Natural Language Processing hit the expectation of growth of more than four million in upcoming years.
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Now, we shall discuss the applications of Natural Language Processing and how these NLP applications are utilized for various purposes.
Applications of Natural Language Processing
Chatbots
Chatbots are a form of AI programmed to communicate, interact or sound like humans. Depending on their complexity, chatbots can either merely respond to specific phrases or even carry on whole conversations that make it tricky to discern them apart from human beings. Natural Language Processing and Machine Learning are used to create chatbots, so they can comprehend the nuances of the English language, determine the true meaning of a text, and learn from interactions with humans as they develop. Chatbots operate in only two easy steps. They first determine the question's intent and gather all user information needed to provide an answer. They then provide a suitable response to the query.
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Autocomplete in Search Engines
We might have experienced that search engines provide the guessing query while we type something on search engines. For example, when you type in Google books, you will get lots of suggestions related to that word. So, all these suggestions we have seen on Google are programmed by Natural Language Processing. Moreover, using Natural Language Processing autocomplete, we get many suggestions to guess what you want to ask.
How we get many search queries when we type a single word, Natural Language Processing tries to connect the relevant keywords and provides many suggestions for searchers. However, When users enter certain words, search engines utilize their massive data sets to determine what their users are likely typing and recommend the most viable options.
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Voice Assistants
As everything becomes a technology, we all might have been using any one of the voice assistance products in our home. These voice assistance devices are now used to automate the process by observing human speech. Voice assistants like Amazon Alexa, Google Assistant, Apple Siri, Microsoft Cortana, and Samsung Bixby are used for making calls, reminders, meeting scheduling, alarms, app interaction, turning on lights, ordering food, and even finding lost phones, etc.
Though we are using it for various purposes, we are unaware of how these are processed. Life has become considerably simpler due to these voice assistants. But how do they function? To comprehend what is being said and then act upon it, they use an intelligent blend of voice recognition, natural language understanding, and natural language processing. Voice assistants' long-term objective is to connect people to the internet and offer various services solely through voice interactions. They are still far from achieving this objective, as Siri occasionally fails to comprehend what you say.
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Language Translator
Applications of natural language processing are utilized in text translation. For example, if you want to translate a text from English to Tamil but you don't know Tamil, Google translator tools are used. Moreover, it is not restricted to any language.
It enables the algorithm to translate a set of words from one language to another. In the past, language translators employed statistical machine translation (SMT), which involved analyzing millions of texts that had already been translated from one language to another and then searching for the language's fundamental patterns and lexicon. However, this approach fell short of sequence-to-sequence modeling in terms of accuracy.
Sentiment Analysis
Nowadays, almost the entire globe uses social media! Additionally, businesses can utilize sentiment analysis to understand how a specific user group feels about a topic, subject, etc. They can employ text analysis, natural language processing, computational linguistics, and other techniques to determine whether users have a positive, negative, or neutral attitude toward their goods and services. Companies can utilize sentiment analysis in various ways, including evaluating customer feedback, determining their target audience's emotions, and assessing their brands' reactions. In addition to commercial businesses, Governments utilize sentiment analysis to identify public opinion and potential dangers to the country's security.
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Grammar Checkers
Applications of natural language processing are used for various purposes, but many of them are using it for grammar checkers. Nowadays, a grammar checker is widely utilized by many professionals. Predominantly it is used by the content writer for checking syntax formation, spelling, grammar usage in sentences, and various purposes. Prominently, it is not only utilized to check spellings; instead, it provides suggestions and synonyms to enhance the readability score and enrich the content.
NLP application algorithms are programmed to provide the best possible suggestions to the user. So, The NLP algorithm is drilled on millions of syntax to comprehend the suitable format. NLP applications have been trained to suggest correct verb tense, synonym, syntax formation, etc. The most well-known NLP-based grammar checkers include Grammarly, WhiteSmoke, ProWritingAid, etc.
Email Classification and Filtering
The most effective method for business communication is Email. Evey small to large enterprise utilizes this communication method to share information. We all have used Email for several purposes and have noticed emails are divided into three sections - Primary, Social, and Promotions.
Email uses applications of natural language processing to analyze each Email's text content to classify it into the appropriate category. Moreover, in complex situations, some businesses now deploy specialized anti-virus software with NLP processing to analyze the emails for patterns and words that might point to an employee phishing attempt.
Now, you would have understood the NLP application (applications of natural language processing) processes and how it is utilized for various purposes. So, to have a profound understanding of NLP project ideas, join a Machine Learning Course and learn how NLP application is in machine learning.