June 17, 2021 Beginner, Listicle, NLP, Python

Must Know Data Pre-processing Techniques for Natural Language Processing!

This article was published as a part of the Data Science Blogathon Introduction Data from the internet forms a huge source of information these days. We have an overwhelming amount of data available, which includes text, audio, and videos. Text information forms a major source of information amongst these. Natural language processing includes the task of analyzing, modifying, and deriving conclusions from text data. These text or speech data are completely unstructured and messy. A great amount of effort is required […]

June 12, 2021 Advanced, Data Science, NLP, Project, Python, PyTorch, Unstructured Data

Language Translation with Transformer In Python!

This article was published as a part of the Data Science Blogathon Introduction Natural Language Processing (NLP) is a field at the convergence of artificial intelligence, and linguistics. The aim is to make the computers understand real-world language or natural language so that they can perform tasks like Question Answering, Language Translation, and many more. NLP has lots of applications in different fields. 1. NLP enables the recognition and prediction of diseases based on electronic health records. 2. It is used […]

June 8, 2021 Deep Learning, Intermediate, NLP, Unstructured Data

Generate Questions from Movies!

This article was published as a part of the Data Science Blogathon Have you ever thought of generating questions from the SRT files of Movies? I don’t know if we can use this but it is pretty exciting when I came to know as a beginner that we can do that. What is SRT? In simple terms, the subtitles you see in Amazon Prime, Netflix, Hotstar, HBO, etc are saved in a text file with (.srt) extension with timestamps. The timestamp […]

June 8, 2021 Beginner, Data Science, Machine Learning, NLP, Python, Text

Text Analytics of Resume Dataset with NLP!

This article was published as a part of the Data Science Blogathon Introduction We all have made our resumes at some point in time. In a resume, we try to include important facts about ourselves like our education, work experience, skills, etc. Let us work on a resume dataset today. The text we put in our resume speaks a lot about us. For example, our education, skills, work experience, and other random information about us are all present in a resume. […]

May 29, 2021 Advanced, Deep Learning, NLP, Text, Unstructured Data

Measuring Text Similarity Using BERT

This article was published as a part of the Data Science Blogathon BERT is too kind — so this article will be touching on BERT and sequence relationships! Abstract A significant portion of NLP relies on the connection in highly-dimensional spaces. Typically an NLP processing will take any text, prepare it to generate a tremendous vector/array rendering said text — then make certain transformations. It’s a highly-dimensional charm. At an exceptional level, there’s not much extra to it. We require to […]

May 27, 2021 NLP, Power BI, Python, Text, Use Cases

Interesting NLP Use Cases Every Data Science Enthusiast should know!

This article was published as a part of the Data Science Blogathon Introduction Natural Language Processing (NLP) is a subpart of Artificial Intelligence that uses algorithms to understand and process human language. Various computational methods are used to process and analyze human language and a wide variety of real-life problems are solved using Natural Language Processing. (Source: Kaggle.com) Using Natural Language Processing, we use machines by making them understand how human language works. Basically, we use text data and make computers analyze […]

May 24, 2021 Beginner, Libraries, NLP, Python, Text, Unstructured Data

Top 8 Python Libraries For Natural Language Processing (NLP) in 2021

This article was published as a part of the Data Science Blogathon. Introduction Natural language processing (NLP) is a field situated at the convergence of data science and Artificial Intelligence (AI) that – when reduced to the basics – is all about teaching machines how to comprehend human dialects and extract significance from the text. This is additionally why Artificial Intelligence is regularly essential for NLP projects. So what’s the reason, why many companies care about NLP? Basically in light […]

May 24, 2021 Advanced, Artificial intelligence, Deep Learning, NLP, PyTorch

BERT for Natural Language Inference simplified in Pytorch!

This article was published as a part of the Data Science Blogathon Introduction to BERT: BERT stands for Bidirectional Encoder Representations from Transformers. It was introduced in 2018 by Google Researchers. BERT achieved state-of-art performance in most of the NLP tasks at that time and drawn the attention of the data science community worldwide. It is extensively used today by data science practitioners for various NLP tasks. Details about the working of the BERT model can be found here. Introduction to […]

May 19, 2021 Deep Learning, Intermediate, NLP, Python, Unstructured Data

SMS Spam Detection Using LSTM – A Hands On Guide!

Introduction In today’s world, almost everyone is using a mobile phone and all of them will receive messages(SMS/ email) daily on their phone. But the main thing is that many of the received messages will be spam and only a few of them are ham or required messages. In this article, we are going to create an SMS spam detection model which will help you to find whether an SMS is spam or not using LSTM. About Dataset: Here we […]

May 17, 2021 Data Science, Intermediate, NLP, Python, Unstructured Data, Unsupervised

Build your own NLP based search engine Using BM25

Introduction Ever wondered how these search engines like Google and Yahoo work. And ever thought about how can they scan all through the internet and return relevant results in just About 5,43,00,000 results (0.004seconds). Well, they work on the concept of Crawling and Indexing. Crawling: Automated bots looks for pages that are new or updated. And stores the key information like — URL, title, keywords, and so on from the pages to be used later. Indexing: Data captured from crawling is analyzed […]

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