Demystifying BERT: A Comprehensive Guide to the Groundbreaking NLP Framework

Overview Google’s BERT has transformed the Natural Language Processing (NLP) landscape Learn what BERT is, how it works, the seismic impact it has made, among other things We’ll also implement BERT in Python to give you a hands-on learning experience   Introduction to the World of BERT Picture this – you’re working on a really cool data science project and have applied the latest state-of-the-art library to get a pretty good result. And boom! A few days later, there’s a […]

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3 Important NLP Libraries for Indian Languages You Should Try Out Today!

Overview Ever wondered how to use NLP models in Indian languages? This article is all about breaking boundaries and exploring 3 amazing libraries for Indian Languages We will implement plenty of NLP tasks in Python using these 3 libraries and work with Indian languages   Introduction Language is a wonderful tool of communication – its powered the human race for centuries and continues to be at the heart of our culture. The sheer amount of languages in the world dwarf […]

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Build Text Categorization Model with Spark NLP

Overview Setting up John Snow labs Spark-NLP on AWS EMR and using the library to perform a simple text categorization of BBC articles. Introduction Natural Language Processing is one of the important processes for data science teams across the globe. With ever-growing data, most of the organizations have already moved to big data platforms like Apache Hadoop and cloud offerings like AWS, Azure, and GCP. These platforms are more than capable of handling    

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Text Mining Simplified – IPL 2020 Tweet Analysis with R

This article was published as a part of the Data Science Blogathon. Introduction Text mining utilizes different AI technologies to automatically process data and generate valuable insights, enabling companies to make data-driven decisions. Text mining identifies facts, relationships, and assertions that would otherwise remain buried in the mass of textual big data. Once extracted, this information is converted into a structured form that can be further analyzed, or presented directly using clustered HTML tables, mind maps, charts, etc. Advantages of […]

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Text Mining hack: Subject Extraction made easy using Google API

Let’s do a simple exercise. You need to identify the subject and the sentiment in following sentences: Google is the best resource for any kind of information. I came across a fabulous knowledge portal – Analytics Vidhya Messi played well but Argentina still lost the match Opera is not the best browser Yes, like UAE will win the Cricket World Cup. Was this exercise simple? Even if this looks like a simple exercise, now imagine creating an algorithm to do this? How does that […]

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Text Classification & Word Representations using FastText (An NLP library by Facebook)

Introduction If you put a status update on Facebook about purchasing a car -don’t be surprised if Facebook serves you a car ad on your screen. This is not black magic! This is Facebook leveraging the text data to serve you better ads. The picture below takes a jibe at a challenge while dealing with text data. Well, it clearly failed in the above attempt to deliver the right ad. It is all the more important to capture the context […]

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Ultimate guide to deal with Text Data (using Python) – for Data Scientists and Engineers

Introduction One of the biggest breakthroughs required for achieving any level of artificial intelligence is to have machines which can process text data. Thankfully, the amount of text data being generated in this universe has exploded exponentially in the last few years. It has become imperative for an organization to have a structure in place to mine actionable insights from the text being generated. From social media analytics to risk management and cybercrime protection, dealing with text data has never […]

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Comprehensive Hands on Guide to Twitter Sentiment Analysis with dataset and code

Introduction Natural Language Processing (NLP) is a hotbed of research in data science these days and one of the most common applications of NLP is sentiment analysis. From opinion polls to creating entire marketing strategies, this domain has completely reshaped the way businesses work, which is why this is an area every data scientist must be familiar with. Thousands of text documents can be processed for sentiment (and other features including named entities, topics, themes, etc.) in seconds, compared to […]

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How to Get Started with NLP – 6 Unique Methods to Perform Tokenization

Overview Looking to get started with Natural Language Processing (NLP)? Here’s the perfect first step Learn how to perform tokenization – a key aspect to preparing your data for building NLP models We present 6 different ways to perform tokenization on text data   Introduction Are you fascinated by the amount of text data available on the internet? Are you looking for ways to work with this text data but aren’t sure where to begin? Machines, after all, recognize numbers, […]

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How Search Engines like Google Retrieve Results: Introduction to Information Extraction using Python and spaCy

Overview How do search engines like Google understand our queries and provide relevant results? Learn about the concept of information extraction We will apply information extraction in Python using the popular spaCy library – so a lot of hands-on learning is ahead!   Introduction I rely heavily on search engines (especially Google) in my daily role as a data scientist. My search results span a variety of queries – Python code questions, machine learning algorithms, comparison of Natural Language Processing […]

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