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🤓All the geeky stuffs you need to know at one place!
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Collection of Useful Algorithms in multiple programming languages and some awesome cheat-sheet and resources for learning geeky stuffs.
- A ridiculous collection of cheatsheets
- Awesome cheatsheets for popular programming languages, frameworks and development tools
- 📓 UI component dev & test: React, Vue, Angular, React Native, Ember, Web Components & more!
- Awesome lists about all kinds of interesting topics
- List of Development YouTube Channels
- 📝 A curated list of Web Performance Optimization
- 💻📖 Laws, Theories, Principles and Patterns that developers will find useful. #hackerlaws
- A Collection of application ideas which can be used to improve your coding skills
- Teach Yourself Computer Science
- 🤓 Build your own (insert technology here)
- Google's Engineering Practices documentation
- A list of Free Software network services and web applications which can be hosted locally
- Real-time performance monitoring, done right!
- 🎓 Path to a free self-taught education in Computer Science!
- 📚 List of awesome university courses for learning Computer Science!
- Deploy a Production Ready Kubernetes Cluster
- 📖 A collection of pure bash alternatives to external processes
- Utility bash scripts to do automatable tasks with a single command
- Git Commands
- Simple terminal UI for git commands
- A gitmoji interactive command line tool for using emojis on commits 💻
#"Permalink: Javascript:" href="#javascript">
- Must-watch videos about javascript
- A curated list of javascript fundamentals and algorithms
- This is about useful JS tips!
- A book about JavaScript, programming, and the wonders of the digital
- 🐢 A collection of awesome browser-side JavaScript libraries, resources and shiny things
- LazyLoad is a fast, lightweight and flexible script that speeds up your web application by loading your content images, videos and iframes only as they enter the viewport
- A book series on JavaScript. @YDKJS on twitter
- A long list of (advanced) JavaScript questions, and their explanations ✨
- jQuery — New Wave JavaScript
- React.js
- lodash - A modern JavaScript utility library delivering modularity, performance, & extras
- Underscore.js - A utility-belt library for JavaScript
- Knockout - A JavaScript MVVM (a modern variant of MVC) library
- Polymer - library which enables cross-browser support for HTML5 web components
- Textures.js is a JavaScript library for creating SVG patterns
- Lightweight fuzzy-search, in JavaScript
- A practical functional library for JavaScript programmers
- A table library that works everywhere
- Angular.js
- Vue.js
- Ext JS
- Backbone.js
- Next.js
- Ember.js - A JavaScript framework for creating ambitious web applications
- Fastify - Fast and low overhead web framework, for Node.js
- Alpine - A rugged, minimal framework for composing JavaScript behavior in your markup
- 📊 Cube.js - Open Source Analytics Framework
- Cool Python features for machine learning
- A collection of Python Scripts made for fun, while exploring Python 🐍
- Tutorials on various Python modules and its applications
- Python Tutorials in Detail
- Momentum
- Adblock Plus
- uBlock Origin
- Wappalyzer
- GitHub Repository Size
- Grammarly
- Isometric Contributions
- WhatFont
- React Developer Tools
- Octotree
- Refined GitHub
- JSON Formatter
- Angular DevTools
- Vue.js devtools
- GoFullPage - Full Page Screen Capture
- Fake Filler
- PyTorch tutorials
- Data-Science Cheat-Sheet
- Related papers for robust machine learning
- Pretrained EfficientNet, MixNet, MobileNetV3, MNASNet A1 and B1, FBNet, Single-Path NAS
- A booklet on machine learning systems design with exercises
- A collection of datasets ready to use with TensorFlow
- code for Data Science From Scratch book
- Tutorials, assignments, and competitions for MIT Deep Learning related courses
- Fast image augmentation library and easy to use wrapper around other libraries
- Collection of Artificial Intelligence Algorithms implemented on various problems
- PyTorch image models, scripts, pretrained weights
- Code for visualizing the loss landscape of neural nets
- Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
- Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
- An end-to-end PyTorch framework for image and video classification
- The simplest way for researchers and developers to build world-class ML solutions
- Pose Animator takes a 2D vector illustration and animates its containing curves in real-time
- A system for detecting human body, facial and foot keypoints from RGB images
- A YouTube channel that covers recent and interest research works in the ML and DL area
- Tensorflow 2.0 cheat sheet
- A list of ML papers, along with their respective code links
- React-Typescript Cheatsheet
- Lint rules related to React & JSX for TSLint
- 🐐 Simple and complete React DOM testing utilities that encourage good testing practices
- React Native Awesome Button
- React Native Awesome Slider
- Simple and complete React DOM testing utilities
- Jest utilities for Styled Components
- Collection of useful React components
- Build forms in React, without the tears 😭
- High performance
<canvas>
rendering for React components - 🌊 A flexible and fun JavaScript file upload library
- A React-Native datetime-picker for Android and iOS
- Galio is a beautifully designed, Free and Open Source React Native Framework
- A description of the conceptual model of React without implementation burden
- Recoil - An experimental state management library for React apps
- The recommended Code Splitting library for React ✂️✨
- A draggable and resizable grid layout with responsive breakpoints, for React
- A collection of beautiful and useful React hooks to speed-up your components and hooks development
- Babylon.js is a powerful, beautiful, simple, and open game and rendering engine packed into a friendly JavaScript framework
- Fast and lightweight WebGL game engine
- Tech interview prep list
A curated awesome list of lists of interview questions. Feel free to contribute! 🎓
- 101+ coding interview problems
- 🕸 Almost complete answers to "Front-end Job Interview Questions" which you can use to interview potential candidates, test yourself or completely ignore
- JavaScript interview Questions
- Data Structures and Algorithms in JavaScript
- Pramp - Practice live interviews with peers
- Coding Interview University
- Interview Company Guides
Can't see your favorite algorithm script or cheat-sheet? Send a PR for adding your favorite algorithm in any programming language.
This repository is available under theMIT License.
Want to check your peers latest commits?Try this out
P.S.: Please make sure the file name itself is self-explanatory about the Algorithm or make a folder along containing your script and a README file explaining the necessary details. Also, make sure there is main(): function which is taking clear inputs(if any) which could be easily understood by any person who wants to use that algorithm.
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