Beginners Guide to Regular Expressions in Natural Language Processing

Introduction Regular Expressions is very popular among programmers and can be applied in many programming languages like Java, JS, php, C++, etc. Regular Expressions are useful for numerous practical day-to-day tasks that a data scientist encounters. It is one of the key concepts of Natural Language Processing that every NLP expert should be proficient in. Regular Expressions are used in various tasks such as data pre-processing, rule-based information mining systems, pattern matching, text feature engineering, web scraping, data extraction, etc. […]

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Sentiment Analysis: Predicting Sentiment Of COVID-19 Tweets

This article was published as a part of the Data Science Blogathon. Introduction Hi folks, I hope you are doing well in these difficult times! We all are going through the unprecedented time of the Corona Virus pandemic. Some people lost their lives, but many of us successfully defeated this new strain i.e. Covid-19. The virus was declared a pandemic by World Health Organization on 11th March 2020. This article will analyze various types of “Tweets” gathered during pandemic times. […]

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Customer Sentiments Analysis of Pepsi and Coca-Cola using Twitter Data in R

This article was published as a part of the Data Science Blogathon. Introduction Coca-Cola and PepsiCo are well-established names in the soft drink industry with both in the fortune 500. The companies that own a wide spectrum of product lines in a highly competitive market have a fierce rivalry with each other and constantly competing for market share in almost all subsequent product verticals. We will analyze the sentiment of customers of these two companies with the help of 5000 […]

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Implementation of Attention Mechanism for Caption Generation on Transformers using TensorFlow

Overview Learning about the state of the art model that is Transformers. Understand how we can implement Transformers on the already seen image captioning problem using Tensorflow Comparing the results of Transformers vs attention models.   Introduction We have seen that Attention mechanisms (in the previous article) have become an integral part of compelling sequence modeling and transduction models in various tasks (such as image captioning), allowing modeling of dependencies without regard to their distance in the input or output […]

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Emotion classification on Twitter Data Using Transformers

Introduction The world of Natural language processing is recently overtaken by the invention of Transformers. Transformers are entirely indifferent to the conventional sequence-based networks. RNNs are the initial weapon used for sequence-based tasks like text generation, text classification, etc. But with the arrival of LSTM and GRU cells, the issue with capturing long-term dependency in the text got resolved. But learning the model with LSTM cells is a hard task as we cannot make it learn parallelly.

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Out-of-the-box NLP functionalities for your project using Transformers Library!

This article was published as a part of the Data Science Blogathon. Introduction In this tutorial, you will learn how you can integrate common Natural Language Processing (NLP) functionalities into your application with minimal effort. We will be doing this using the ‘transformers‘ library provided by Hugging Face. 1. First, Install the transformers library. # Install the library !pip install transformers 2. Next, import the necessary functions. # Necessary imports from transformers import pipeline 3. Irrespective of the task that […]

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Fake news classifier on US Election News📰 | LSTM 🈚

Introduction News media has become a channel to pass on the information of what’s happening in the world to the people living. Often people perceive whatever conveyed in the news to be true. There were circumstances where even the news channels acknowledged that their news is not true as they wrote. But some news has a significant impact not only on the people or    

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Hands-On Tutorial on Stack Overflow Question Tagging

This article was published as a part of the Data Science Blogathon. Background I won’t be lying if I assert that every developer/engineer/student has used the website Stack Overflow more than once in their journey. Widely considered as one of the largest and more trusted websites for developers to learn and share their knowledge, the website presently hosts in excess of 10,000,000 questions. In this post, we try to predict the question tags based on the question text asked on […]

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Step by step guide to extract insights from free text (unstructured data)

Text Mining is one of the most complex analysis in the industry of analytics. The reason for this is that, while doing text mining, we deal with unstructured data. We do not have clearly defined observation and variables (rows and columns). Hence, for doing any kind of analytics, you need to first convert this unstructured data into a structured dataset and then proceed with normal modelling framework. The additional step of converting an unstructured data into a structured format is […]

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How do Transformers Work in NLP? A Guide to the Latest State-of-the-Art Models

Overview The Transformer model in NLP has truly changed the way we work with text data Transformer is behind the recent NLP developments, including Google’s BERT Learn how the Transformer idea works, how it’s related to language modeling, sequence-to-sequence modeling, and how it enables Google’s BERT model   Introduction I love being a data scientist working in Natural Language Processing (NLP) right now. The breakthroughs and developments are occurring at an unprecedented pace. From the super-efficient ULMFiT framework to Google’s […]

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