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 […]

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Implementing Transformers in NLP Under 5 Lines Of Codes

This article was published as a part of the Data Science Blogathon Introduction Today, we will see a gentle introduction to the transformers library for executing state-of-the-art models for complex NLP tasks. Applying state-of-the-art Natural Language Processing models has never been more straightforward. Hugging Face has revealed a compelling library called transformers that allow us to perform and use a broad class of state-of-the-art NLP models in a specific way. Today we are operating to install and use the transformers library […]

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Can Python understand human feelings through words? – A brief intro to NLP and VADER Sentiment Analysis

This article was published as a part of the Data Science Blogathon Introduction Imagine having the power to observe your customer’s thoughts, like what they really think of a particular product/service. For instance, there is a new product launched by NIKE and REEBOK. Both the companies launched a pair of new sports shoes and posted them on their social media accounts like Instagram or Facebook for marketing purposes. Is it possible for an individual to check all the thousands or lakhs […]

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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 […]

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Machine Learning Automation using EvalML Library

This article was published as a part of the Data Science Blogathon Introduction Machine Learning is one of the fastest-growing technology in the modern era. New innovations in the field of ML and AI are made each and every day which supports the world to leap forward. Earlier for a person entering into the ML field finds it difficult to create accurate machine learning models, but now AutoML Libraries are created which helps the beginners to create an accurate model with […]

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Automate NLP Tasks using EvalML Library

“The quality of your communication shapes the quality of your life.”, with this beautiful line let’s s begin and understand what we will learn in this article. In my one of the article, I have explained how to automate machine learning problem statement using EvalML. In this article we will look at “is it possible to automate NLP task using EvalML?”. What is EvalML? It is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective […]

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Introduction to Hugging Face’s Transformers v4.3.0 and its First Automatic Speech Recognition Model – Wav2Vec2

Overview Hugging Face has released Transformers v4.3.0 and it introduces the first Automatic Speech Recognition model to the library: Wav2Vec2 Using one hour of labeled data, Wav2Vec2 outperforms the previous state of the art on the 100-hour subset while using 100 times less labeled data Using just ten minutes of labeled data and pre-training on 53k hours of unlabeled data Wav2Vec2 achieves 4.8/8.2 WER Understand Wav2Vec2 implementation using transformers library on audio to text generation   Introduction Transformers has been […]

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Step by step guide to building sentiment analysis model using graphlab

I have been using graph lab for quite some time now. The first Kaggle competition I used it for was Click Trough Rate (CTR) and I was amazed to see the speed at which it can crunch such big data. Over last few months, I have realised much broader applications of GraphLab. In this article I will take up the text mining capability of GraphLab and solve one of the Kaggle problems. I will be referring to this problem with […]

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Natural Language Processing Made Easy – using SpaCy (​in Python)

Introduction Natural Language Processing is one of the principal areas of Artificial Intelligence. NLP plays a critical role in many intelligent applications such as automated chat bots, article summarizers, multi-lingual translation and opinion identification from data. Every industry which exploits NLP to make sense of unstructured text data, not just demands accuracy, but also swiftness in obtaining results. Natural Language Processing is a capacious field, some of the tasks in nlp are – text classification, entity detection, machine translation, question […]

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Introduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library

Introduction Last couple of years have been incredible for Natural Language Processing (NLP) as a domain! We have seen multiple breakthroughs – ULMFiT, ELMo, Facebook’s PyText, Google’s BERT, among many others. These have rapidly accelerated the state-of-the-art research in NLP (and language modeling, in particular). We can now predict the next sentence, given a sequence of preceding words. What’s even more important is that machines are now beginning to understand the key element that had eluded them for long. Context! Understanding context […]

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