Category: Natural Language Processing
Interesting applications of blockchain in ML and NLP?
In recent years, the blockchain has been used to track and store information on a variety of applications. It can be used to store data about transactions, contracts or other records in a secure way. Blockchain is decentralized and not controlled by any single entity. This makes it an ideal technology for machine learning algorithms.…
Read MoreHow Blockchain can be used in Natural Language Processing?
The blockchain is a revolutionary technology which has the potential to change how we do business. It can be used in many different fields and industries, but one of the most interesting applications is in Natural Language Processing. The blockchain has the potential to revolutionize how data is stored and shared. It can store data…
Read MoreWhat is the future of Natural Language Processing in healthcare?
With the development of natural language processing (NLP) and machine learning, natural language processing in healthcare is becoming more and more important. NLP is a computer programming technique that uses statistical techniques to analyse text or speech and extract meaning from it. It has been used for many years in computational linguistics but only recently…
Read MoreHow does sentiment analysis work
Sentiment analysis is a natural language processing technique that analyses the sentiment of a text. It is used in many applications, such as opinion mining and customer feedback. Sentiment analysis is an increasingly popular research topic in the field of computer science. It’s a process that entails three major parts: sentiment analysis, sentiment classification, and…
Read MoreWhat are the Challenges of Natural Language Processing
Natural Language Processing is that the field of design methods and algorithms that takes as input or produce as output unstructured. Human language is highly ambiguous (consider the sentence I ate pizza with friends, and compare it to I ate pizza with olives), and also highly variable (the core message of I ate pizza with…
Read MoreStemming vs Lemmatization Difference: Explained in Detail
Introduction When dealing with large amount of text data, it becomes essential to preprocess and analyze the text effectively. Stemming and lemmatization are text processing techniques that help reduce words to their base forms, helps you in better analysis and understanding. Stemming Stemming is a technique that aims to reduce words to their root form,…
Read MoreTokenization in NLP: Breaking Language into Meaningful Words
Tokenization is a fundamental concept in Natural Language Processing (NLP) that involves breaking down text into smaller tokens. Whether you’ve heard of tokenization before or not, this article will help you get the clear and concise explanation. What is Tokenization? Tokenization is the process of dividing a given text, such as a document, paragraph, or…
Read MoreDifference between Deep Learning and Natural Language Processing?
In the realm of artificial intelligence, two prominent domains, Deep Learning (DL) and Natural Language Processing (NLP), have emerged as powerful tools. While both are related to machine learning, they serve distinct purposes and possess unique characteristics. This article aims to delve into the dissimilarities between Deep Learning and Natural Language Processing, shedding light on…
Read MoreHow does Natural Language Processing work?
Machine learning algorithms are great at providing excellent insights. They’re perfect for spotting patterns we didn’t observe before we were able to make predictions with them. They’re tailor-made for specific scenarios and put many algorithms to use, allowing machines to perform a lot of our jobs. It can be hard to process such large amounts…
Read MoreWhat is Natural Language Processing and its Applications and Capabilities
Introduction The field of Natural Language Processing (NLP) has completely transformed the way computers comprehend, analyze, and produce human language. This revolutionary discipline encompasses the understanding of spoken conversations and text messages, making it possible for applications like Siri and Alexa to read messages and provide intelligent responses. Moreover, NLP has found its usefulness across…
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