Articles About Natural Language Processing

July 8, 2021 Advanced, Classification, Libraries, NLP, Project, Python, Structured Data, Supervised, Text

Sentiment Analysis using NLTK – A Practical Approach

This article was published as a part of the Data Science Blogathon Introduction The ultimate goal of this blog is to predict the sentiment of a given text using python where we use NLTK aka Natural Language Processing Toolkit, a package in python made especially for text-based analysis. So with a few lines of code, we can easily predict whether a sentence or a review(used in the blog) is a positive or a negative review. Before moving on to the implementation […]

July 8, 2021 Classification, News, NLP, Project, Python, Text

Build Your Own Fake News Classifier With NLP

img src: https://wallpapercave.com/w/wp7461543 Introduction The major objective of watching or reading news was to be informed about whatever is happening around us. There are several social media platforms in the current modern era, like Facebook, Twitter, Reddit, and so forth where millions of users would rely upon for knowing day-to-day happenings. Then came the fake news which spread across people as fast as the real news could. Fake news is a piece of incorporated or falsified information often aimed at misleading […]

July 8, 2021 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 […]

July 1, 2021 NLP

Dynabench: Rethinking Benchmarking in NLP

June 10, 2021 By: Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams Abstract We introduce Dynabench, an open-source platform for dynamic dataset creation and model benchmarking. Dynabench runs in a web browser and supports human-and-model-in-the-loop dataset creation: annotators seek to create examples that a target model will misclassify, but that […]

June 30, 2021 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 […]

June 30, 2021 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 […]

June 29, 2021 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 […]

June 28, 2021 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 […]

June 28, 2021 NLP, Terminology

Issue #136 – Neural Machine Translation without Embeddings

28 Jun21 Issue #136 – Neural Machine Translation without Embeddings Author: Dr. Jingyi Han, Machine Translation Scientist @ Language Weaver Introduction Nowadays, Byte Pair Encoding (BPE) has become one of the most commonly used tokenization strategies due to its universality and effectiveness in handling rare words. Although many previous works show that subword models with embedding layers in general achieve more stable and competitive results in neural machine translation (NMT), character-based (see issue #60) and Byte-based subword (see issue #64) […]

June 27, 2021 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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