Tag: nlp

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. […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
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 […]

Read more
Beginner, Machine Learning, NLP, Unstructured Data, Unsupervised

Topic Modeling and Latent Dirichlet Allocation(LDA) using Gensim and Sklearn : Part 1

This article was published as a part of the Data Science Blogathon Introduction Let’s say you have a client who has a publishing house. Your client comes to you with two tasks: one he wants to categorize all the books or the research papers he receives weekly on a common theme or a topic and the other task is to encapsulate large documents into smaller bite-sized texts. Is there any technique and tool available that can do both of these two […]

Read more
1 2 3 4 5 … 15