Category: Advanced

Advanced, Data Engineering, Docker, Machine Learning, Model Deployment, NLP, Profile Building

Deploying Machine learning Application on AWS Fargate

Amazon Web Services(AWS) offers reliable, scalable, and cost-effective cloud computing services. It provides Infrastructure as a service(IaaS), Platform as a Service(PaaS), Software as a Service(SaaS) also a new model known as Function as a Service(FaaS) eg. AWS Lambda which is a serverless entity. Before going further, if you don’t have an AWS account please create one to follow along with the hands-on. Amazon Elastic Container Service(ECS) Amazon ECS is a container orchestration platform developed by Amazon, it is similar to […]

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Advanced, NLP, Project, Python, Structured Data, Text

Text Preprocessing made easy!

This article was published as a part of the Data Science Blogathon Introduction We will learn the basics of text preprocessing in this article. Humans communicate using words and hence generate a lot of text data for companies in the form of reviews, suggestions, feedback, social media, etc. A lot of valuable insights can be generated from this text data and hence companies try to apply various machine learning or deep learning models to this data to gain actionable insights. Text […]

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Advanced, NLP, Project, Python, Structured Data, Text

NLP Application: Named Entity Recognition (NER) in Python with Spacy

Natural Language Processing deals with text data. The amount of text data generated these days is enormous. And, this data if utilized properly can bring many fruitful results. Some of the most important Natural Language Processing applications are Text Analytics, Parts of Speech Tagging, Sentiment Analysis, and Named Entity Recognition. The vast amount of text data contains a huge amount of information. An important aspect of analyzing these text data is the identification of Named Entities. What is a Named […]

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Advanced, Data Science, NLP, Python, Text

A Gentle Introduction To MuRIL : Multilingual Representations for Indian Languages

This article was published as a part of the Data Science Blogathon “MuRIL is a starting point of what we believe can be the next big evolution for Indian language understanding. We hope it will prove to be a better foundation for researchers, startups, students, and anyone else interested in building Indian language technologies” said Partha Talukdar, Research Scientist, Google Research India. What is MuRIL? MuRIL, short for Multilingual Representations for Indian Languages, is none other than a free and open-source […]

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Advanced, NLP, Programming, Project, Python, Supervised, Technique, Text, Use Cases

TS-SS similarity for Answer Retrieval from Document in Python

This article was published as a part of the Data Science Blogathon Introduction This article focuses on answer retrieval from a document by using a similarity algorithm. This task falls under Natural Language Processing which is a subset of Deep Learning. In this article, we will be understanding why do we require better techniques and what are the drawbacks of using naive algorithms. Moreover, we will be implementing a similarity-based technique for answer retrieval from the document. This article is a […]

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Advanced, NLP, Project, Python, Text, Unstructured Data

Why and how to use BERT for NLP Text Classification?

This article was published as a part of the Data Science Blogathon Introduction NLP or Natural Language Processing is an exponentially growing field. In the “new normal” imposed by covid19, a significant proportion of educational material, news, discussions happen through digital media platforms. This provides more text data available to work upon! Originally, simple RNNS (Recurrent Neural Networks) were used for training text data. But in recent years there have been many new research publications that provide state-of-the-art results. One of […]

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Advanced, NLP

Part 12: Step by Step Guide to Master NLP – Grammar in 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 the previous article, we discussed some basic concepts related to syntactic analysis. In that article, we covered concepts such as parsing, parse trees, and parsers, etc. But we not discussed the concept of grammar in that article. So, In continuation to that article, we will complete a Syntactic analysis in this article. So, […]

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Advanced, NLP, Project, Python, Text, Unsupervised

Part 10: Step by Step Guide to Master NLP – Named Entity Recognition

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, we discussed semantic analysis, which is a level of NLP tasks. In that article, we discussed the techniques of Semantic analysis in which we discussed one technique named entity extraction, which is very important to understand in NLP. So, In this article, we will deep dive into the entity extraction […]

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Advanced, NLP, Project, Python, Text

Part 1: Step by Step Guide to Master NLP – Introduction

This article was published as a part of the Data Science Blogathon Introduction Computers and Machines are great while working with tabular data or Spreadsheets. However, human beings generally communicate in words and sentences, not in the form of tables or spreadsheets, and most of the information that humans speak or write is present in an unstructured manner. So it is not very understandable for computers to interpret these languages. Therefore, In natural language processing (NLP), our aim is to make […]

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Advanced, Computer Vision, Image, Image Analysis, NLP, Project, Python, Unstructured Data

Text detection from images using EasyOCR: Hands-on guide

# Changing the image path IMAGE_PATH = ‘Turkish_text.png’ # Same code here just changing the attribute from [‘en’] to [‘zh’] reader = easyocr.Reader([‘tr’]) result = reader.readtext(IMAGE_PATH,paragraph=”False”) result Output: [[[[89, 7], [717, 7], [717, 108], [89, 108]], ‘Most Common Texting Slang in Turkish’], [[[392, 234], [446, 234], [446, 260], [392, 260]], ‘test’], [[[353, 263], [488, 263], [488, 308], [353, 308]], ‘yazmak’], [[[394, 380], [446, 380], [446, 410], [394, 410]], ‘link’], [[[351, 409], [489, 409], [489, 453], [351, 453]], ‘bağlantı’], [[[373, 525], […]

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