Beginner, Data Science, Libraries, NLP, Python, Text

Text Analysis with Spacy to Master NLP techniques

This article was published as a part of the Data Science Blogathon Natural Language Processing(NLP) is a branch of Artificial Intelligence that deals with Daily Language. Have you ever wonder how Alexa, Siri, Google Assistant understand us with voice and respond to us. Human Language is the fuzziest and complex. As they receive text input first preprocessing of text happens and many techniques are embedded which lets them understand grammar. In this tutorial, we will study some techniques which are helpful […]

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Data Science, Intermediate, NLP, Python, Text, Unstructured Data

Part 7: Step by Step Guide to Master NLP – Word Embedding in Detail

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 articles (part-5 and 6), we completed the different text vectorization and word embeddings techniques in detail. In this article, firstly we will discuss the co-occurrence matrix, which is also a word vectorization technique and after that, we will be discussing new concepts related to the Word embedding that includes, Applications of […]

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Advanced, Algorithm, NLP, Text

Word Sense Disambiguation: Importance in Natural Language Processing

This article was published as a part of the Data Science Blogathon Introduction In human language, often a word is used in more than one way. Understanding the various usage patterns in the language is important for various Natural Language Processing Applications. ( Image: https://www.pexels.com/photo/book-eyeglasses-eyewear-page-261857/ ) In various usage situations, the same word can mean differently. As, a vast majority of the information online, is in English, for the sake of simplicity, let us deal with examples in the English language only. […]

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Data Science, Intermediate, Libraries, NLP, Python, Text, Word Embeddings

Practical Guide to Word Embedding System

This article was published as a part of the Data Science Blogathon Pre-requisites – Basic knowledge of Python – Understanding of basics of NLP(Natural Language Processing)   Introduction In natural language processing, word embedding is used for the representation of words for Text Analysis, in the form of a vector that performs the encoding of the meaning of the word such that the words which are closer in that vector space are expected to have similar in mean. Consider, boy-men vs […]

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

Part 3: Topic Modeling and Latent Dirichlet Allocation (LDA) using Gensim and Sklearn

This article was published as a part of the Data Science Blogathon Overview In the previous two installments, we had understood in detail the common text terms in Natural Language Processing (NLP), what are topics, what is topic modeling, why it is required, its uses, types of models and dwelled deep into one of the important techniques called Latent Dirichlet Allocation (LDA). In this last leg of the Topic Modeling and LDA series, we shall see how to extract topics through […]

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Beginner, Data Science, Machine Learning, NLP, Unstructured Data

Understanding Natural Language Processing -A Beginner’s Guide

This article was published as a part of the Data Science Blogathon Introduction:   Source: https://www.asksid.ai/blog/what-is-natural-language-processing/ Language is very important when we want to communicate with each other. Every human can talk and tell others what they need and listen with language. These languages can be anything like English, Spanish, Hindi, Malayalam, etc… We can express our ideas to others in this medium. Language is one of the critical components of human intelligence. Every day we interact with humans, but how about […]

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Numpy

Creating a Linear Program Solver by Implementing the Simplex Method in Python

Simplex-Numpy Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy The example in Simplex.py is : [ 0 2 1 ] A = [ 0 1 1 ] b = [ 20 18 8 ] c = [ 1 -7 -4 ] [ 0 1 0 ] And I already test some random inputs with the use of random function in Numpy: A = np.random.randint(-25, 25,size = (SIZE_MATRIX_X, SIZE_MATRIX_Y)) b = np.random.randint(-25, 25,size = SIZE_MATRIX_X) […]

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Command-line Tools

A command line tool for displaying Python source and bytecode

dis-cli Display Python source code and bytecode side-by-side at the command line dis-cli is a command line tool for displaying Python source and bytecode. Installation dis-cli can be installed from PyPI. To install via pip, run $ pip install dis-cli Usage dis-cli provides a command line program, dis, which takes a “import-like” path to a function to display information about. For example, if you have a package a, with a submodule b, containing a function c, you could run dis […]

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Bot

Chatbot for ordering and tracking a Pizza

Pizza Chatbot To start the app, follow the below steps: Clone the repo using the below command: git clone [email protected]:shreyashah115/PizzaHere.git Go to the cloned directory, create a virtaul environment and activate it: cd PizzaHere/ virtualenv -p python3 myenv source myenv/bin/activate pip3 install -r requirements.txt Start the server using the below command: python3 manage.py runserver How the chatbot works: The bot will reply to your small talk questions at the beginning of the flow as shown below, You can place a […]

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Command-line Tools

A CLI-based program that checks the file’s integrity

SHA-ZAM – Check the file hash sum Shazam is a Command Line Application that checks the integrity of one file by comparing it with a given hash. Created by: Anaxímeno Brito How Does It Work: It calculates the file’s hash sum and compares it with a given hash for checking if the file isn’t corrupted, it can also be used for calculating the hash sums and automatically save it inside one file if wanted. Shazam supports some of the most […]

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