Discord

Pycord, a maintained fork of discord.py, is a python wrapper for the Discord API

A fork of discord.py. PyCord is a modern, easy to use, feature-rich, and async ready API wrapper for Discord written in Python. Key Features Modern Pythonic API using async and await. Proper rate limit handling. Optimised for both speed and memory usage. Supports Slash Commands, Context Menus and Message Components. Installing Python 3.8 or higher is required To install the library without full voice support, you can just run the following command:

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Papers

The implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets

This is the implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets. abstract: We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical […]

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Games

A Tetris Game for programming education

プログラミング学習を目的とした、ブロックを操作してスコアを競うゲームです。FAQはこちら。tutorialはこちら。 実行環境準備 Mac環境 Finder→Application→Utility→Terminalから、ターミナルを起動して以下コマンドを実行する。 # install pyqt5 and NumPy brew install python3 pip3 install pyqt5 pip3 install numpy # install other packages brew install git doc/files/install_mac.mdに上記手順を記載 Ubuntu/JetsonNano環境 doc/files/install_ubuntu.mdに手順を記載 windows環境 WSL(Windows Subsystem for Linux)を使う場合の手順Docker for Windowsを使う場合の手順 docker環境 docker/README.mdに手順を記載 実行方法 本リポジトリを取得 cd $HOME git clone https://github.com/seigot/tetris_game ゲーム開始用スクリプトを実行

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Django

AUES Student Management System Developed for laboratory works №9 Purpose using Python (Django)

AUES Student Management System Developed for laboratory works №9 Purpose using Python (Django).Feel free to make changes based on your requirements. I’ve created this project while learnging Django and followed tutorial series from Youtube & Books And if you like this project then ADD a STAR ⭐️ to this project 👆 Features of this Project A. Admin Users Can See Overall Summary Charts of Stuudents Performance, Staffs Perfomrances, Courses, Subjects, Leave, etc. Manage Staffs (Add, Update and Delete) Manage Students […]

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Scratch

Scratch2py or S2py is a easy to use, versatile tool to communicate with the Scratch API Based of Scratch2py

Scratch2py or S2py is a easy to use, versatile tool to communicate with the Scratch APIBased of Scratch2py Installation Run this command in your terminal as ONE command. pip install scratch2py && pip install –force-reinstall websocket-client Usage Import scratch2py in like this: from scratch2py import Scratch2Py s2py = Scratch2Py(‘username’, ‘password’) # Imports s2py and initializes    

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Cracker

Latest Facebook Crack Tools

[1] pkg update && pkg upgrade [2] pkg install git [3] pkg install python [4] pkg install python2 [5] pkg install nano [6] pip install futures [7] pip2 install futures [8] pip install mechanize [9] pip2 install mechanize [10] pip install requests [11] pip2 install requests [12] git clone https://github.com/mrjeeck/JMBFF [13] pip2 install ipaddress [14] git pull [15] cd JMBFF [16] python2 JMBFF.py    

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Python

Binary, Bytes, and Bitwise Operators in Python

Computers store all kinds of information as a stream of binary digits called bits. Whether you’re working with text, images, or videos, they all boil down to ones and zeros. Python’s bitwise operators let you manipulate those individual bits of data at the most granular level. Python isolates you from the underlying bits with high-level abstractions. You’re more likely to find the overloaded flavors of bitwise operators in practice. But when you work with them in their original form, you’ll […]

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NLP

Course Recommendations for Introductory Machine Learning

Before you jump into deep learning, I would strongly advise you to do a few introductory machine learning courses to get up to speed with fundamental concepts like clustering, regression, evaluation metrics, etc.  Here is a thread including a few recent courses you can explore: This is a crosspost of a Twitter thread I published earlier this week. Elements of AI by University of Helsinki Note: I have taken many machine learning courses online. I do some courses for fun […]

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