Beginner’s Guide To Text Classification Using PyCaret

Introduction Have you ever solved a Machine Learning problem in just one go? Solving a problem using machine learning isn’t straightforward. It involves various steps to come up with an accurate solution. The process/steps to be followed for solving an ml problem is known as ML Pipeline/ML Cycle. ML Pipeline/ ML Cycle (Credits: https://medium.com/analytics-vidhya/machine-learning-development-life-cycle-dfe88c44222e) As shown in the figure, the Machine Learning pipeline consists of different steps like: Understand Problem Statement, Hypothesis Generation, Exploratory Data Analysis, Data Preprocessing, Feature Engineering, […]

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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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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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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 […]

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Topic Modelling in Natural Language Processing

Introduction Natural language processing is the processing of languages used in the system that exists in the library of nltk where this is processed to cut, extract and transform to new data so that we get good insights into it. It uses only the languages that exist in the library because NLP-related things exist there itself so it cannot understand the things beyond what is present in it. If you do processing on another language then you have to add […]

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Beginners Guide to Topic Modeling in Python

Introduction Analytics Industry is all about obtaining the “Information” from the data. With the growing amount of data in recent years, that too mostly unstructured, it’s difficult to obtain the relevant and desired information. But, technology has developed some powerful methods which can be used to mine through the data and fetch the information that we are looking for. One such technique in the field of text mining is Topic Modelling. As the name suggests, it is a process to […]

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Text Mining 101: A Stepwise Introduction to Topic Modeling using Latent Semantic Analysis (using Python)

Introduction Have you ever been inside a well-maintained library? I’m always incredibly impressed with the way the librarians keep everything organized, by name, content, and other topics. But if you gave these librarians thousands of books and asked them to arrange each book on the basis of their genre, they will struggle to accomplish this task in a day, let alone an hour! However, this won’t happen to you if these books came in a digital format, right? All the […]

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