A Hands-on Tutorial to Learn Attention Mechanism For Image Caption Generation in Python

Overview Understand the attention mechanism for image caption generation Implement attention mechanism to generate caption in python   Introduction The attention mechanism is a complex cognitive ability that human beings possess. When people receive information, they can consciously ignore some of the main information while ignoring other secondary information. This ability of self-selection is called attention. The attention mechanism allows the neural network to have the ability to focus on its subset of inputs to select specific features.  In recent […]

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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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How to create a poet / writer using Deep Learning (Text Generation using Python)?

Introduction From short stories to writing 50,000 word novels, machines are churning out words like never before. There are tons of examples available on the web where developers have used machine learning to write pieces of text, and the results range from the absurd to delightfully funny. Thanks to major advancements in the field of Natural Language Processing (NLP), machines are able to understand the context and spin up tales all by themselves.               […]

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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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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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Create a Pipeline to Perform Sentiment Analysis using NLP

This article was published as a part of the Data Science Blogathon. Overview Every basic fundamental and building block which is required for Sentiment Analysis. I’ve used an easy approach to explain all the basic concepts so that even a beginner reader would be able to get a thorough understanding of all the concepts. Topics: Preprocessing text, Vocabulary Corpus, Feature Extraction (Sparse Representation and Frequency Dictionary), Logistic Regression model for sentiment analysis.   Sentiment Analysis is a supervised Machine Learning […]

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An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec

Introduction Before we start, have a look at the below examples. You open Google and search for a news article on the ongoing Champions trophy and get hundreds of search results in return about it. Nate silver analysed millions of tweets and correctly predicted the results of 49 out of 50 states in 2008 U.S Presidential Elections. You type a sentence in google translate in English and get an Equivalent Chinese conversion.   So what do the above examples have […]

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A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text

Introduction I work on different Natural Language Processing (NLP) problems (the perks of being a data scientist!). Each NLP problem is a unique challenge in its own way. That’s just a reflection of how complex, beautiful and wonderful the human language is. But one thing has always been a thorn in an NLP practitioner’s mind is the inability (of machines) to understand the true meaning of a sentence. Yes, I’m talking about context. Traditional NLP techniques and frameworks were great when […]

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An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP

Overview Neural fake news (fake news generated by AI) can be a huge issue for our society This article discusses different Natural Language Processing methods to develop robust defense against Neural Fake News, including using the GPT-2 detector model and Grover (AllenNLP) Every data science professional should be aware of what neural fake news is and how to combat it   Introduction Fake news is a major concern in our society right now. It has gone hand-in-hand with the rise […]

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