Building a FAQ Chatbot in Python – The Future of Information Searching

Introduction What do we do when we need any information? Simple: “We Ask, and Google Tells”. But if the answer depends on multiple variables, then the existing Ask-Tell model tends to sputter. State of the art search engines usually cannot handle such requests. We would have to search for information available in bits and pieces and then try to filter and assemble relevant parts together. Sounds time consuming, doesn’t it? Source: Inbenta This Ask-Tell model is evolving rapidly with the […]

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A Comprehensive Guide to Understand and Implement Text Classification in Python

Improving Text Classification Models While the above framework can be applied to a number of text classification problems, but to achieve a good accuracy some improvements can be done in the overall framework. For example, following are some tips to improve the performance of text classification models and this framework. 1. Text Cleaning : text cleaning can help to reducue the noise present in text data in the form of stopwords, punctuations marks, suffix variations etc. This article can help to understand how […]

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Introduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library

Introduction Last couple of years have been incredible for Natural Language Processing (NLP) as a domain! We have seen multiple breakthroughs – ULMFiT, ELMo, Facebook’s PyText, Google’s BERT, among many others. These have rapidly accelerated the state-of-the-art research in NLP (and language modeling, in particular). We can now predict the next sentence, given a sequence of preceding words. What’s even more important is that machines are now beginning to understand the key element that had eluded them for long. Context! Understanding context […]

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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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Innoplexus Sentiment Analysis Hackathon: Top 3 Out-of-the-Box Winning Approaches

Overview Hackathons are a wonderful opportunity to gauge your data science knowledge and compete to win lucrative prizes and job opportunities Here are the top 3 approaches from the Innoplexus Sentiment Analysis Hackathon – a superb NLP challenge   Introduction I’m a big fan of hackathons. I’ve learned so much about data science from participating in these hackathons in the past few years. I’ll admit it – I have gained a lot of knowledge through this medium and this, in […]

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People to Follow in the field of Natural Language Processing (NLP)

Overview Text analytics is becoming easier with many people working day and night on each aspect of Natural Language Processing We list a set of people to follow in the field NLP Feel we should include anyone else? Let us know!   Introduction Natural Language Processing has made unstructured text data analysis simpler. With numerous applications, NLP is affecting and adding values to millions of lives. But the problem NLP practitioners face is catching up with the changes that happen […]

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Fine-Grained Sentiment Analysis of Smartphone Review

How to conduct fine-grained sentiment analysis: Approaches and Tools Data collection and preparation. For data collection, we scraped the top 100 smartphone reviews from Amazon using python, selenium, and beautifulsoup library. If you don’t know how to use python and beautifulsoup and request a library for web-scraping here is a quick tutorial. Selenium Python bindings provide a simple API to write functional/acceptance tests using Selenium WebDriver. Let’s begin coding    

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Ultimate Guide to Understand and Implement Natural Language Processing (with codes in Python)

Overview Complete guide on natural language processing (NLP) in Python Learn various techniques for implementing NLP including parsing & text processing Understand how to use NLP for text feature engineering   Introduction According to industry estimates, only 21% of the available data is present in structured form. Data is being generated as we speak, as we tweet, as we send messages on Whatsapp and in various other activities. Majority of this data exists in the textual form, which is highly unstructured […]

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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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