Category: Python

Python tutorials

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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Python

Python vs JavaScript for Python Developers

Python isn’t the only language out there, and one of the other languages frequently fighting Python for the top of the “most popular” lists is JavaScript. JavaScript is the de facto language on the web but also has a robust toolset on the server side. This course explores JavaScript from a Python programmer’s perspective. If you’ve never used JavaScript before or have felt overwhelmed by the quick pace of its evolution in recent years, then this course will set you […]

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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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Beginner, Data Cleaning, NLP, Python, Text

Part 4: Step by Step Guide to Master NLP – Text Cleaning Techniques

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 part of this blog series, we complete the initial steps involved in text cleaning and preprocessing that are related to NLP. Now, in continuation of that part, in this article, we will cover the next techniques involved in the NLP pipeline of Text preprocessing. In this article, we will first discuss […]

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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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Python

Simplify Complex Numbers With Python

Most general-purpose programming languages have either no support or limited support for complex numbers. Your typical options are learning some specialized tool like MATLAB or finding a third-party library. Python is a rare exception because it comes with complex numbers built in. Despite the name, complex numbers aren’t complicated! They’re convenient in tackling practical problems that you’ll get a taste of in this tutorial. You’ll explore vector graphics and sound frequency analysis, but complex numbers can also help in drawing […]

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

All You Need to know about BERT

This article was published as a part of the Data Science Blogathon Introduction Machines understand language through language representations. These language representations are in the form of vectors of real numbers. Proper language representation is necessary for a better understanding of the language by the machine. Language representations are of two types: (i) Context-free language representation such as Glove and Word2vec where embeddings for each token in the vocabulary are constant and it doesn’t depend on the context of the word. […]

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

Analyzing customer feedbacks using Aspect Based Sentiment Analysis

This article was published as a part of the Data Science Blogathon Introduction With the advancement in technology, the growth of social media like Facebook, Twitter, Instagram has been a platform for the customers to give feedback to the businesses based on their satisfaction. The reviews posted by customers are the globally trusted source of genuine content for other users. Customer feedback serves as the third-party validation tool to build user trust in the brand. For understanding these customer feedbacks […]

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Beginner, Data Cleaning, NLP, Python, Text, Unstructured Data, Word Embeddings

Part- 6: Step by Step Guide to Master Natural Language Processing (NLP) in Python

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 […]

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Advanced, NLP, Project, Python, Text

Part- 1: Step by Step Guide to Master Natural Language Processing (NLP) in Python

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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