Bot

A multipurpose Telegram Bot writen in Python for mirroring files

Deepak Clouds Mirror Deepak Clouds Torrent is a multipurpose Telegram Bot writen in Python for mirroring files on the Internet to our beloved Google Drive. Additional Features Get detailed info about replied media (Only for Telegram file) Speedtest with picture results Stop duplicate cloning Google Drive Mega support Added Limiting size Torrent/Direct, Mega, cloning Google Drive support Sudo with Database support Multiple Trackers support Extracting tar.xz support Create Tar Google Drive folder Counting file/folder Shell and Executor View Link button […]

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Discord

A discord bot consuming Notion API to add and retrieve data from Notion databases

Notion-DiscordBot A discord bot consuming Notion API to add and retrieve data from Notion databases. Instructions to use the bot: Pre-Requisites: a)Install all the requirements using pip3 install -r requirements.txt b)Create a discord bot using the developer platform of discord and obtain your OAuth2 token. Keep it somewhere safe c)Go to Notion and create a new Integration https://www.notion.so/my-integrationsNote the internal Integration. d)Go to Notion and create a table like this: 4 columns where: Contributor is of property type Title URL […]

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Optimization

Enhanced Particle Swarm Optimization (PSO) with Python

pso_particle_swarm_optimization Implemented fully documented Particle Swarm Optimization (PSO) algorithm in Python which includes a basic model along with few advanced features such as updating inertia weight, cognitive, social learning coefficients and maximum velocity of the particle. Implemented fully documented Particle Swarm Optimization (PSO) algorithm in Python which includes a basic model along with few advanced features such as updating inertia weight, cognitive, social learning coefficients and maximum velocity of the particle. Dependencies Utilities Once the installation is finished (download or […]

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Advanced, NLP, Project, Python, Text

Part 3: Step by Step Guide to NLP – Text Cleaning and Preprocessing

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 part-1and  part-2 of this blog series, we complete the theoretical concepts related to NLP. Now, in continuation of that part, in this article, we will cover some of the new concepts. In this article, we will understand the terminologies required and then we start our journey towards text cleaning and preprocessing, which is […]

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

Part 6: Step by Step Guide to Master NLP – Word2Vec

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, Listicle, NLP, Programming, Python

Regex Cheatsheet For Natural Language Processing tasks

This article was published as a part of the Data Science Blogathon Introduction Regex is a shorthand for Regular Expression. It is a representation for a set, a set of strings. Say we have a list of emails and we want to check if they are in the correct format or not. One way is to check each and every mail manually but that’s not possible if the number of mails is quite high. So, regex here comes to your rescue. […]

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Advanced, NLP, Python, Text, Unstructured Data

Part 13: Step by Step Guide to Master NLP – Regular Expressions

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). From this article, we will start our discussion on Regular Expressions. When a data scientist comes across a text processing problem whether it is searching for titles in names or dates of birth in a dataset, regular expressions rear their ugly head very frequently. They form part of the basic techniques in NLP and […]

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Data Science, Libraries, NLP, Python, Text, Unstructured Data

Part 2: Topic Modeling and Latent Dirichlet Allocation (LDA) using Gensim and Sklearn

This article was published as a part of the Data Science Blogathon Introduction In the previous article, we had started with understanding the basic terminologies of text in Natural Language Processing(NLP), what is topic modeling, its applications, the types of models, and the different topic modeling techniques available. Let’s continue from there, explore Latent Dirichlet Allocation (LDA), working of LDA, and its similarity to another very popular dimensionality reduction technique called Principal Component Analysis (PCA).   Table of Contents A Little […]

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Beginner, Libraries, NLP, Python, Text, Topic Modeling

Topic modeling With Naive Bayes Classifier

This article was published as a part of the Data Science Blogathon Introduction Naive Bayes is a powerful tool that leverages Bayes’ Theorem to understand and mimic complex data structures. In recent years, it has commonly been used for Natural Language Processing (NLP) tasks, such as text categorization. Today, we will be constructing a Naive Bayes text classifier for topic categorization. Before we move forward with the explanation, I want to emphasize that Naive Bayes is not the traditional method of […]

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processing

A Python library for processing and analysis of electron backscatter diffraction patterns

kikuchipy kikuchipy is an open-source Python library for processing and analysis of electron backscatter diffraction (EBSD) patterns. The library builds on the tools for multi-dimensional data analysis provided by the HyperSpy library. User guide and API reference: https://kikuchipy.org. The guide consists of Jupyter Notebooks with many links to detailed explanations of the input parameters and output of functions and class methods (the API reference). The notebooks can be inspected statically on the web page or via nbviewer, downloaded and run […]

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