Category: Unsupervised

Advanced, Data Exploration, Data Visualization, NLP, Python, Text, Unstructured Data, Unsupervised

WhatsApp Group Chat Analysis using Python

Introduction Today one of the trendy social media platforms is…. guess what? One and only Whatsapp😅. It is one of the favorite social media platforms among all of us because of its attractive features. It has more than 2B users worldwide and “According to one survey an average user spends more than 195 minutes per week on WhatsApp”. How terrible the above statement is. Leave all these things and let’s understand what actually WhatsApp analyzer means? WhatsApp Analyzer means we […]

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Advanced, Data Exploration, Data Visualization, NLP, Project, Python, Technique, Text, Unsupervised

Speed Up Text Pre Processing Using TextHero Python Library

Introduction     Natural Language Processing, typically abbreviated as NLP, is a branch of artificial intelligence that manages the connection among PCs and people utilizing the regular language. A definitive target of NLP is to peruse, unravel, comprehend, and figure out the human dialects in a way that is significant. Most NLP strategies depend on AI to get significance from human dialects. NLP involves applying calculations to recognize and separate the characteristic language decides to such an extent that the […]

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Beginner, NLP, Python, Technique, Text, Unsupervised

A Simple Guide to Metrics for Calculating String Similarity

Introduction One of the applications of Natural Language Processing is auto-correction and spellings checks. All of us have encountered this that if we type an incorrect or typo in the Google search engine, then the engine automatically corrects it and suggests the right word in its place. How does the engine do that? How does it know what word we wanted to write or ask? That is what we will be covering in this article. The methods available to check […]

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Advanced, NLP, Unsupervised, Videos

Tokenization and Text Normalization

Objective Text data is a type of unstructured data used in natural language processing. Understand how to preprocess the text data before feeding it to the machine learning algorithms. Introduction Text data is a form of unstructured data. The most prominent examples of text data available on the internet are social media data like tweets, posts, comments, or the Conversation data such as messages, emails, Chats. Also, it can be article data like news articles, blogs, etc. Note: If you […]

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Advanced, NLP, Python, Technique, Text, Unstructured Data, Unsupervised Leave a comment

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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Advanced, Classification, NLP, Project, R, Social Media, Technique, Text, Unstructured Data, Unsupervised Leave a comment

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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Advanced, NLP, Project, Python, Resource, Text, Unstructured Data, Unsupervised, Use Cases Leave a comment

How to create your own Question and Answering API(Flask+Docker +BERT) using haystack framework

Introduction Note from the author: In this article, we will learn how to create your own Question and Answering(QA) API using python, flask, and haystack framework with docker. The haystack framework will provide the complete QA features which are highly scalable and customizable. In this article Medium Rules, the text will be used as the target document and fine-tuning the model as well. Basic Knowledge Required: Elasticsearch & Docker This article contains the working code which can be directly build […]

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Advanced, Data Exploration, NLP, Python, Resource, Text, Unstructured Data, Unsupervised, Use Cases Leave a comment

Analysis of Brazilian E-commerce Text Review Dataset Using NLP and Google Translate

This article was published as a part of the Data Science Blogathon. Introduction Comprehending the reviews of customers is very crucial for a business to be successful. Analyzing the reviews helps to properly discern the customer different preferences, likes, dislikes, etc. These extracted insights can then be used to improve customer service and experience.  In this article, we would be working on a Brazilian E-commerce reviews dataset where we would perform some exploratory data analysis (EDA) on reviews text, derive […]

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Advanced, NLP, Python, Social Media, Technique, Text, Unstructured Data, Unsupervised Leave a comment

Summarize Twitter Live data using Pretrained NLP models

Introduction Twitter users spend an average of 4 minutes on social media Twitter. On an average of 1 minute, they read the same stuff. It shows that users spend around 25% of their time reading the same stuff. Also, most of the tweets will not appear on your dashboard. You may get to know the trending topics, but you miss not trending topics. In trending topics, you might only read the top 5 tweets and their comments. So, what are […]

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Advanced, Deep Learning, NLP, Project, Python, Text, Unstructured Data, Unsupervised Leave a comment

Tired of Reading Long Articles? Text Summarization will make your task easier!

This article was published as a part of the Data Science Blogathon. Introduction Millions of web pages and websites exist on the Internet today. Going through a vast amount of content becomes very difficult to extract information on a certain topic. Google will filter the search results and give you the top ten search results, but often you are unable to find the right content that you need. There is a lot of redundant and overlapping data in the articles […]

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