Part 9: Step by Step Guide to Master NLP – Semantic 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 some important tasks of NLP. I hope after reading that article you can understand the power of NLP in Artificial Intelligence. So, in this part of this series, we will start our discussion on Semantic analysis, which is a level of the NLP tasks, and see all the […]

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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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TS-SS similarity for Answer Retrieval from Document in Python

This article was published as a part of the Data Science Blogathon Introduction This article focuses on answer retrieval from a document by using a similarity algorithm. This task falls under Natural Language Processing which is a subset of Deep Learning. In this article, we will be understanding why do we require better techniques and what are the drawbacks of using naive algorithms. Moreover, we will be implementing a similarity-based technique for answer retrieval from the document. This article is a […]

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All You Need to know about BERT

This article was published as a part of the Data Science Blogathon Introduction Machines understand language through language representations. These language representations are in the form of vectors of real numbers. Proper language representation is necessary for a better understanding of the language by the machine. Language representations are of two types: (i) Context-free language representation such as Glove and Word2vec where embeddings for each token in the vocabulary are constant and it doesn’t depend on the context of the word. […]

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Automate NLP Tasks using EvalML Library

“The quality of your communication shapes the quality of your life.”, with this beautiful line let’s s begin and understand what we will learn in this article. In my one of the article, I have explained how to automate machine learning problem statement using EvalML. In this article we will look at “is it possible to automate NLP task using EvalML?”. What is EvalML? It is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective […]

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Building a Conversational Bot using LUIS

Introduction Companies are increasingly inclining towards having chatbots for their businesses for multiple applications. Amongst the numerous API providers in the chatbot landscape that focus on Natural Language Programming (NLP) and Natural Language Understanding (NLU), I would be demonstrating how to build a chatbot that can automate the process of scheduling interviews using Microsoft’s LUIS. Scheduling interviews comes with a lot of challenges like finding out a suitable slot for everyone, including other participants, rescheduling an interview on a participant’s […]

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Speed Up Text Pre Processing Using TextHero Python Library

Introduction     Natural Language Processing, typically abbreviated as NLP, is a branch of artificial intelligence that manages the connection among PCs and people utilizing the regular language. A definitive target of NLP is to peruse, unravel, comprehend, and figure out the human dialects in a way that is significant. Most NLP strategies depend on AI to get significance from human dialects. NLP involves applying calculations to recognize and separate the characteristic language decides to such an extent that the […]

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A Simple Guide to Metrics for Calculating String Similarity

Introduction One of the applications of Natural Language Processing is auto-correction and spellings checks. All of us have encountered this that if we type an incorrect or typo in the Google search engine, then the engine automatically corrects it and suggests the right word in its place. How does the engine do that? How does it know what word we wanted to write or ask? That is what we will be covering in this article. The methods available to check […]

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A Guide to Feature Engineering in NLP

Overview Feature engineering in NLP is understanding the context of the text. In this blog, we will look at some of the common feature engineering in NLP. We will compare the results of a classification task with and without doing feature engineering   Table of Content Introduction NLP task overview List of features with code Implementation Results comparison with and without doing feature engineering Conclusion Introduction   “If 80 percent of our work is data preparation, then ensuring data quality […]

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Language Detection Using Natural Language Processing

Introduction Every Machine Learning enthusiast has a dream of building/working on a cool project, isn’t it? Mere understandings of the theory aren’t enough, you need to work on projects, try to deploy them, and learn from them. Moreover, working on specific domains like NLP gives you wide opportunities and problem statements to explore. Through this article, I wish to introduce you to an amazing project, the Language Detection model using Natural Language Processing. This will take you through a real-world […]

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