Tag: nlp
Some examples of simple gradient-based NLP models.
There are a lot of simple gradient-based NLP models that can be used to solve a variety of natural language processing tasks. Some of these include: Part-of-speech tagging: sentence parsing is a task that assigns part of speech tags to words in text and is used to analyze sentences. A task that assigns part of…
Read MoreHow is NLP revolutionizing financial services?
NLP is revolutionizing the way we interact with financial services. It’s allowing us to have a more natural conversation with our banks, and this is allowing us to do things that we couldn’t do before. How did you get into NLP? I got into NLP because I had a need, but it turns out that…
Read MoreWhat is bag of words?
We are going to talk about a Natural Language Processing concept called the Bag of words model. When you’re applying an algorithm in NLP, it works with numbers and not words or sentences. We can’t feed our text directly into algorithms like that in order to analyze text data, it needs to be converted into…
Read MoreWhat is Stop word in NLP?
Stop words are the most common words in any language that do not carry any meaning and are usually ignored by NLP. In English, examples of stop words are “a”, “and”, “the” and “of”. In NLP, stop words are typically removed from a text before it is processed for analysis. This is done to reduce…
Read MoreWhat are the Different Applications of NLP in the Real World?
NLP is a branch of artificial intelligence. It is used to analyze and understand human language. NLP has many applications in the real world that can be used for different purposes. Some of these applications include: Natural Language Processing (NLP) is a technique for understanding the sentiment in text. NLP can be utilized to identify…
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 More