Category: Advanced

Advanced, NLP, Project, Python, Text

Part 3: Step by Step Guide to NLP – Text Cleaning and Preprocessing

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 part-1and  part-2 of this blog series, we complete the theoretical concepts related to NLP. Now, in continuation of that part, in this article, we will cover some of the new concepts. In this article, we will understand the terminologies required and then we start our journey towards text cleaning and preprocessing, which is […]

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Advanced, Listicle, NLP, Programming, Python

Regex Cheatsheet For Natural Language Processing tasks

This article was published as a part of the Data Science Blogathon Introduction Regex is a shorthand for Regular Expression. It is a representation for a set, a set of strings. Say we have a list of emails and we want to check if they are in the correct format or not. One way is to check each and every mail manually but that’s not possible if the number of mails is quite high. So, regex here comes to your rescue. […]

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Advanced, NLP, Python, Text, Unstructured Data

Part 13: Step by Step Guide to Master NLP – Regular Expressions

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). From this article, we will start our discussion on Regular Expressions. When a data scientist comes across a text processing problem whether it is searching for titles in names or dates of birth in a dataset, regular expressions rear their ugly head very frequently. They form part of the basic techniques in NLP and […]

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Advanced, NLP, Project, Python, Text, Unstructured Data

Part 2: Step by Step Guide to NLP – Knowledge Required to Learn NLP

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 part-1 of this blog series, we complete the basic concepts of NLP. Now, in continuation of that part, in this article, we will cover some of the new concepts. In this article, we will understand the knowledge required and levels of NLP in a detailed manner. In the last of this article, we […]

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Advanced, conversational AI, NLP

Memory Networks for Q&A(Question and Answer) Applications

This article was published as a part of the Data Science Blogathon Introduction This article shows the power of Memory Networks for Question and Answer (QA) applications in the context of simple natural language-based reasoning. Table of Contents What is the motivation behind Memory Networks? Why do we need Memory Networks when traditional NLP models are already performing well? Facebook bAbI dataset About Supporting Fact Components of Memory Networks How can we find the best match? How does the dot product […]

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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 […]

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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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Advanced, NLP

Part 11: Step by Step Guide to Master NLP – Syntactic Analysis

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 article, we discussed an entity extraction technique named i.e, Named Entity Recognition. There is also another entity extraction technique which is also a popular technique named Topic Modeling, which we will discuss in the subsequent articles of our blog series. So, In this article, we will deep dive into Syntactic Analysis, […]

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