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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Natural Language Processing for Beginners: Using TextBlob

Introduction Natural Language Processing (NLP) is an area of growing attention due to increasing number of applications like chatbots, machine translation etc. In some ways, the entire revolution of intelligent machines in based on the ability to understand and interact with humans. I have been exploring NLP for some time now.  My journey started with NLTK library in Python, which was the recommended library to get started at that time. NLTK is a perfect library for education and research, it becomes […]

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Tutorial on Text Classification (NLP) using ULMFiT and fastai Library in Python

Introduction Natural Language Processing (NLP) needs no introduction in today’s world. It’s one of the most important fields of study and research, and has seen a phenomenal rise in interest in the last decade. The basics of NLP are widely known and easy to grasp. But things start to get tricky when the text data becomes huge and unstructured. That’s where deep learning becomes so pivotal. Yes, I’m talking about deep learning for NLP tasks – a still relatively less […]

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Extracting information from reports using Regular Expressions Library in Python

Introduction Many times it is necessary to extract key information from reports, articles, papers, etc. For example names of companies – prices from financial reports, names of judges – jurisdiction from court judgments, account numbers from customer complaints, etc. These extractions are part of Text Mining and are essential in converting unstructured data to a structured form which are later used for applying analytics/machine learning. Such entity extraction uses approaches like ‘lookup’, ‘rules’ and ‘statistical/machine learning’. In ‘lookup’ based approaches, […]

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Introduction to StanfordNLP: An Incredible State-of-the-Art NLP Library for 53 Languages (with Python code)

Introduction A common challenge I came across while learning Natural Language Processing (NLP) – can we build models for non-English languages? The answer has been no for quite a long time. Each language has its own grammatical patterns and linguistic nuances. And there just aren’t many datasets available in other languages. That’s where Stanford’s latest NLP library steps in – StanfordNLP. I could barely contain my excitement when I read the news last week. The authors claimed StanfordNLP could support more […]

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Introductory guide to Information Retrieval using kNN and KDTree

Introduction I love cricket as much as I love data science. A few years back (on 16 November 2013 to be precise), my favorite cricketer – Sachin Tendulkar retired from International Cricket. I spent that entire day reading articles and blogs about him on the web. By the end of the day, I had read close to 50 articles about him. Interestingly, while I was reading these articles – none of the websites suggested me articles outside of Sachin or cricket. […]

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FlashText – A library faster than Regular Expressions for NLP tasks

People like me working in the field of Natural Language Processing almost always come across the task of replacing words in a text. The reasons behind replacing the words may be different. Some of them are. “would’ve” and “would have” represent the same thing. So changing all the occurrences of “would’ve” to “would have” is one such task. Changing all Case Variations to a single form i.e Python, pytHon, pYthon, pythoN etc. to python Changing all the synonyms of a word to […]

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Introduction to Structuring Customer complaints explained with examples

Introduction In past, if you were not particularly happy with a service or a product, you would go to the service provider or the shop and lodge a complaint. With services-businesses going online and due to enormous scale, lodging complaints in-person may not be always possible. Electronic ways such as emails, social media and particularly websites like www.consumercomplaints.in focusing on such issues, are widely used platforms to vent out the anger as well as publicizing the issue in expectancy of […]

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Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

Introduction PyTorch v TensorFlow – how many times have you seen this polarizing question pop up on social media? The rise of deep learning in recent times has been fuelled by the popularity of these frameworks. There are staunch supporters of both, but a clear winner has started to emerge in the last year. PyTorch was one of the most popular frameworks in 2018. It quickly became the preferred go-to deep learning framework among researchers in both academia and the […]

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