Part 16 : Step by Step Guide to Master NLP – Topic Modelling using LSA

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 completed a basic technique of Topic Modeling named Non-Negative Matrix Factorization. So, In continuation of that part now we will start our discussion on another Topic modeling technique named Latent Semantic Analysis. So, In this article, we will deep dive into a Topic Modeling technique named Latent Semantic Analysis […]

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Part 20: Step by Step Guide to Master NLP – Information Retrieval

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 completed our discussion on Topic Modelling Techniques. Now, in this article, we will be discussing an important application of NLP in Information Retrieval. So, In this article, we will discuss the basic concepts of Information Retrieval along with some of the models that are used in Information Retrieval. NOTE: […]

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Spam Detection – An application of Deep Learning

This article was published as a part of the Data Science Blogathon What each big tech company wants is the Security and Safety of its customers. By detecting spam alerts in emails and messages, they want to secure their network and enhance the trust of their customers. The official messaging app of Apple and the official chatting app of Google i.e Gmail is unbeatable examples of such applications where the process of spam detection and filtering works well to protect users […]

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Getting Started with Natural Language Processing using Python

This article was published as a part of the Data Science Blogathon Why NLP? Natural Language Processing has always been a key tenet of Artificial Intelligence (AI). With the increase in the adoption of AI, systems to automate sophisticated tasks are being built. Some of these examples are described below. Diagnosing rare form of cancer –  At the University of Tokyo’s Institute of Medical Science, doctors used artificial intelligence to successfully diagnose a rare type of leukemia. The doctors used an AI […]

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Feature Extraction and Embeddings in NLP: A Beginners guide to understand Natural Language Processing

This article was published as a part of the Data Science Blogathon Introduction In Natural Language Processing, Feature Extraction is one of the trivial steps to be followed for a better understanding of the context of what we are dealing with. After the initial text is cleaned and normalized, we need to transform it into their features to be used for modeling. We use some particular method to assign weights to particular words within our document before modeling them. We go […]

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Indexing in Natural Language Processing for Information Retrieval

This article was published as a part of the Data Science Blogathon Overview This blog covers GREP(Global-Regular-Expression-Print) and its drawbacks Then we move on to Document Term Matrix and Inverted Matrix Finally, we end with dynamic and distributed indexing image source-https://javarevisited.blogspot.com/2011/06/10-examples-of-grep-command-in-unix-and.html#axzz6zwakOXgt     Global Regular Expression Print Whenever we are dealing with a small amount of data, we can use the grep command very efficiently. It allows us to search one or more files for lines that contain a pattern. For […]

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Let’s Understand How does a chatbot work ?

Introduction A technology that makes the interaction between humans and machines in natural language possible, is an Artificial Intelligence Chatbot! They act like a typical search engine but with more enhanced features. Applications of Artificial Intelligence Chatbots are spread over various domains including eCommerce, healthcare, education, travel, automation, finance, hospitality, insurance, and so on. The chatbots are domain-specific and do what they are intended for.  The applications in their domain include: answering customer queries, booking services like flights, movie tickets, […]

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FuzzyWuzzy Python Library: Interesting Tool for NLP and Text Analytics

This article was published as a part of the Data Science Blogathon Introduction There are many ways to compare text in python. But, often we search for an easy way to compare text. Comparing text is needed for various text analytics and Natural Language Processing purposes. One of the easiest ways of comparing text in python is using the fuzzy-wuzzy library. Here, we get a score out of 100, based on the similarity of the strings. Basically, we are given the similarity […]

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Word Sense Disambiguation: Importance in Natural Language Processing

This article was published as a part of the Data Science Blogathon Introduction In human language, often a word is used in more than one way. Understanding the various usage patterns in the language is important for various Natural Language Processing Applications. ( Image: https://www.pexels.com/photo/book-eyeglasses-eyewear-page-261857/ ) In various usage situations, the same word can mean differently. As, a vast majority of the information online, is in English, for the sake of simplicity, let us deal with examples in the English language only. […]

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Part 3: Topic Modeling and Latent Dirichlet Allocation (LDA) using Gensim and Sklearn

This article was published as a part of the Data Science Blogathon Overview In the previous two installments, we had understood in detail the common text terms in Natural Language Processing (NLP), what are topics, what is topic modeling, why it is required, its uses, types of models and dwelled deep into one of the important techniques called Latent Dirichlet Allocation (LDA). In this last leg of the Topic Modeling and LDA series, we shall see how to extract topics through […]

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