Category: NLP

Articles About Natural Language Processing

Beginner, Machine Learning, NLP, Python, Text, Topic Modeling

Topic extraction From Prime Minister Modi’s Speech

This article was published as a part of the Data Science Blogathon INTRODUCTION Artificial Intelligence (AI) has been a trendy term among individuals for many years. Earlier, when we used to hear the term “AI”, we could only think about Robots. However AI is not limited to robots, and nowadays, every electronic device we use has AI associated with it, be it smartphones, smart TVs, refrigerators, or Air conditioners. AI basically means a machine can take its decision without human intervention. […]

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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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Beginner, Data Cleaning, NLP, Python, Text, Unstructured Data, Word Embeddings

Part 6: Step by Step Guide to Master NLP – Word2Vec

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 of this series, we completed the statistical or frequency-based word embedding techniques, which are pre-word embedding era techniques. So, in this article, we will discuss the recent word-era embedding techniques. NOTE: In recent word-era embedding, there are many such techniques but in this article, we will discuss only the Word2Vec […]

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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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Data Science, Libraries, NLP, Python, Text, Unstructured Data

Part 2: Topic Modeling and Latent Dirichlet Allocation (LDA) using Gensim and Sklearn

This article was published as a part of the Data Science Blogathon Introduction In the previous article, we had started with understanding the basic terminologies of text in Natural Language Processing(NLP), what is topic modeling, its applications, the types of models, and the different topic modeling techniques available. Let’s continue from there, explore Latent Dirichlet Allocation (LDA), working of LDA, and its similarity to another very popular dimensionality reduction technique called Principal Component Analysis (PCA).   Table of Contents A Little […]

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Beginner, Libraries, NLP, Python, Text, Topic Modeling

Topic modeling With Naive Bayes Classifier

This article was published as a part of the Data Science Blogathon Introduction Naive Bayes is a powerful tool that leverages Bayes’ Theorem to understand and mimic complex data structures. In recent years, it has commonly been used for Natural Language Processing (NLP) tasks, such as text categorization. Today, we will be constructing a Naive Bayes text classifier for topic categorization. Before we move forward with the explanation, I want to emphasize that Naive Bayes is not the traditional method of […]

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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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Beginner, Data Cleaning, Machine Learning, NLP, Python, Text, Word Embeddings

Part 5: Step by Step Guide to Master NLP – Word Embedding and Text Vectorization

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). Up to the previous part of this article series, we almost completed the necessary steps involved in text cleaning and normalization pre-processing. After that, we will convert the processed text to numeric feature vectors so that we can feed it to computers for Machine Learning applications. NOTE: Some concepts included in the pipeline of […]

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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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