Category: Text

Clustering, NLP, Project, Python, Text, Topic Modeling

Topic Modelling With LDA -A Hands-on Introduction

This article was published as a part of the Data Science Blogathon Introduction Imagine walking into a bookstore to buy a book on world economics and not being able to figure out the section of the store that has this book, assuming the bookstore has simply stacked all types of books together. You then realize how important it is to divide the bookstore into different sections based on the type of book. Topic Modelling is similar to dividing a bookstore based […]

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Extract city and country mentions from Text like GeoText without regex

flashgeotext Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick implementation. Flashgeotext is a fast, batteries-included (and BYOD) and native python library that extracts one or more sets of given city and country names (+ synonyms) from an input text. Usage from flashgeotext.geotext import GeoText geotext = GeoText() input_text = ”’Shanghai. The Chinese Ministry of Finance in Shanghai said that China plans to cut tariffs on $75 billion worth of goods […]

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BARTScore: Evaluating Generated Text as Text Generation

BARTScore Evaluating Generated Text as Text Generation. Background There is a recent trend that leverages neural models for automated evaluation in different ways, as shown in Fig.1. (a) Evaluation as matching task. Unsupervised matching metrics aim to measure the semantic equivalence between the reference and hypothesis by using a token-level matching functions in distributed representation space (e.g. BERT) or discrete string space (e.g. ROUGE). (b) Evaluation as regression task. Regression-based metrics (e.g. BLEURT) introduce a parameterized regression layer, which would […]

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Beginner, Machine Learning, NLP, Project, Python, Text

Beginner Projects to Learn Natural Language Processing using Python !

This article was published as a part of the Data Science Blogathon Machines understanding language fascinates me, and that I often ponder which algorithms Aristotle would have accustomed build a rhetorical analysis machine if he had the possibility. If you’re new to Data Science, getting into NLP can seem complicated, especially since there are many recent advancements within the field. it’s hard to grasp where to begin. Table of Contents 1.What can Machines Understand? 2.Project 1:Word Cloud 3.Project 2:Spam Detection 4.Project […]

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Beginner, Libraries, NLP, Python, Text, Unstructured Data

Beginner’s Guide To Natural Language Processing Using SpaCy

This article was published as a part of the Data Science Blogathon Pre-requisites Basic Knowledge of Natural Language Processing Hands-on practice of Python Introduction As we know data has some kind of meaning in its position. For every moment, mostly text data is getting generated in different formats like SMS, reviews, Emails, and so on. The main purpose of this article is to understand the basic idea of NLP using the library- SpaCy. So let’s go ahead. In this article, we […]

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Advanced, Classification, NLP, Project, Python, Structured Data, Supervised, Text

Automated Spam E-mail Detection Model(Using common NLP tasks)

Hope you all are doing Good !!! Welcome to my blog! Today we are going to understand about basics of NLP with the help of the Email Spam Detection dataset. We see some common NLP tasks that one can perform easily and how one can complete an end-to-end project. Whether you know NLP or not, this guide should help you as a ready reference. For the dataset used click on the above link or here. Let’s get started, Natural Language […]

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Advanced, NLP, Text

Part 18: Step by Step Guide to Master NLP – Topic Modelling using LDA (Probabilistic Approach)

This article was published as a part of the Data Science Blogathon Introduction This article is part of an ongoing blog series on Natural Language Processing (NLP).  In the previous part of this series, we completed our discussion on pLSA, which is a probabilistic framework for Topic Modelling. But we have seen some of the limitations of pLSA, so to resolve those limitations LDA comes into the picture. So, In this article, we will discuss the probabilistic or Bayesian approach to […]

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Advanced, Classification, NLP, Programming, Project, Python, Supervised, Technique, Text, Use Cases

Amazon Product review Sentiment Analysis using BERT

This article was published as a part of the Data Science Blogathon Introduction Natural Language processing, a sub-field of machine learning has gained immense popularity in the last 5 years in both research and industrial applications due to the advancement in the field of deep learning and improvement in the computational power of hardware systems. It is a technique for computers to understand how human languages work involving the usage of computational linguistics and the computer science domain. In recent years, […]

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Saliency-based Span Mixup for Text Classification

SSMix Saliency-based Span Mixup for Text Classification (Findings of ACL 2021) Abstract Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text consists of discrete tokens with variable length. In this work, we propose SSMix, a novel mixup method where the operation is performed on input text rather than on hidden vectors like previous approaches. SSMix synthesizes a sentence […]

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Print text color and text format on Term with Python

term-printer Print ‘text color’ and ‘text format’ on Term with Python ※ It may not work depending on the OS and shell used. PIP $ pip install term-printer import from term_printer import Color, Color256, ColorRGB, StdText, cprint If you want to override bultin print function from term_printer import Color, Color256, ColorRGB, StdText, cprint as print Usage 1. Attrs print Applies to all characters. You can specify Format, Color, Color256, and ColorRGB. Able to specify more than one. source from term_printer […]

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