Category: Python

Python tutorials

Beginner, Libraries, NLP, Python, Text, Unstructured Data

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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Python

Measuring the memory usage of a Pandas DataFrame

How much memory are your Pandas DataFrame or Series using? Pandas provides an API for measuring this information, but a variety of implementation details means the results can be confusing or misleading. Consider the following example: >>> import pandas as pd >>> series = pd.Series([“abcdefhjiklmnopqrstuvwxyz” * 10 … for i in range(1_000_000)]) >>> series.memory_usage() 8000128 >>> series.memory_usage(deep=True) 307000128 Which is correct, is memory usage 8MB or 300MB? Neither! In this special case, it’s actually 67MB, at least with the default […]

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Python

Python Inner Functions

Python allows the declaration of functions inside of other functions. Inner functions, also known as nested functions, are defined within a function. This type of function has direct access to variables and names defined in the enclosing function in Python. Inner functions have many uses, most notably as closure factories and decorator functions. In this course, you’ll learn how to: Define inner functions Use inner functions as helper functions Build function closures Use captured variables in a closure Use captured […]

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

Automated Spam E-mail Detection Model(Using common NLP tasks)

Hope you all are doing Good !!! Welcome to my blog! Today we are going to understand about basics of NLP with the help of the Email Spam Detection dataset. We see some common NLP tasks that one can perform easily and how one can complete an end-to-end project. Whether you know NLP or not, this guide should help you as a ready reference. For the dataset used click on the above link or here. Let’s get started, Natural Language […]

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Python

Reverse Python Lists: Beyond .reverse() and reversed()

Sometimes you need to process Python lists starting from the last element down to the first—in other words, in reverse order. In general, there are two main challenges related to working with lists in reverse: To meet the first challenge, you can use either .reverse() or a loop that swaps items by index. For the second, you can use reversed() or a slicing operation. In the next sections, you’ll learn about different ways to accomplish both in your code. Reversing […]

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

Amazon Product review Sentiment Analysis using BERT

This article was published as a part of the Data Science Blogathon Introduction Natural Language processing, a sub-field of machine learning has gained immense popularity in the last 5 years in both research and industrial applications due to the advancement in the field of deep learning and improvement in the computational power of hardware systems. It is a technique for computers to understand how human languages work involving the usage of computational linguistics and the computer science domain. In recent years, […]

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Beginner, Data Science, NLP, Python, Text, Word Embeddings

Part 8: Step by Step Guide to Master NLP – Useful Natural Language Processing Tasks

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). Up to part-7 of this series, we completed the most useful concepts in NLP. While going away in this series, let’s first discuss some of the useful tasks of NLP so that you have much clarity about what you can do by learning the NLP. After this part, we will start our discussion on […]

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Deep Learning, Libraries, NLP, Python, Unsupervised

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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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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