davidmensahedem/helpful-resources

a curated list of resources for devs

Instructions

📍 Fork and Clone the Repo

📍 Create a new branch

📍 What to do? Fairly Simple! You find an amazing resource or tool, you drop the link here ❤️

📍 Put it under an appropriate category ( web, mobile etc... ) with a brief description.

📍 If it doesn't fit under any, create a befitting one.

📍 Make a Pull Request with Main branch to submit your additions.

📍 Let's go

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WEB

CSS

• layout it
  create grid layouts with ease

• create clip paths
  easier way to create clip paths

• blob maker
  generate svg blobs

• waves
  generate svg waves

• haikei
  generate svg assets

• animate
  generate key frames for animation

• css box shadows
  get a variety of box-shadow values

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MOBILE

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AI-ML

• Machine Learning with Andrew Ng.: This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition.

• Machine Learning roadmap with curated courses

  • Getting started
    • Neural Networks
    • Deep Learning from the foundations
    • NYU Deep Learning Spring 2021
    • MIT RES.LL-005 Mathematics of Big Data and Machine Learning (by Jeremy Kepner and Vijay Gadepally)
    • Stanford CS229: Machine Learning (by @AndrewYNg)
    • Stanford CS230: Deep Learning (by Andrew Ng)
    • Machine Learning Course for Beginners (by Ayush Singh and @freecodecamp)
  • Computer vision
    • Stanford CS231n Convolutional Neural Networks for Visual Recognition (by @karpathy)
    • Convolutional Neural Networks (by Andrew Ng)
    • Advanced Computer Vision with Python (by Murtaza Hassan and freecodecamp)
    • OpenCV Python Course - Learn Computer Vision and AI (by @LearnOpenCV and freecodecamp)
    • Tensorflow Object Detection in 5 Hours with Python (by @nicholasrenotte)
  • NLP
    • Stanford CS224N: NLP with Deep Learning (by @chrmanning)
    • Natural Language Processing with TensorFlow 2 - Beginner's Course (by Phil Tabor and freecodecamp)
    • Intro to NLP with spaCy (by @explosion_ai)
  • Reinforcement learning
    • Stanford CS234: Reinforcement Learning (by @EmmaBrunskill)
    • Reinforcement Learning Course - Full Machine Learning Tutorial (by Phil Tabor and freecodecamp)
    • Deep Reinforcement Learning in Python Tutorial - A Course on How to Implement Deep Learning Papers (by Phil Tabor and freecodecamp)
    • Reinforcement Learning in 3 Hours (by @nicholasrenotte)
  • Applications
    • MIT 6.S897 Machine Learning for Healthcare (by @david_sontag and Peter Szolovits)
    • Applied Deep Learning with PyTorch (by Fawaz Sammani and freecodecamp)
    • Algorithmic Trading Using Python - Full Course (by @NickJMcCullum and freecodecamp)
    • Machine Learning for Trading at Georgia Tech (by @tuckerbalch)
    • MIT Machine Learning in Genomics (by @manoliskellis)
    • Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis (by @thedataprof and freecodecamp)

• Coding

  • Python
    • MIT 6.0001 Introduction to Computer Science and Programming in Python (by @anabellphd)
    • Learn Python - Full Course for Beginners (by @mike_dane and freecodecamp)
    • Python for Data Science - Course for Beginners (by freecodecamp and Maxwell Armi)
  • R
    • R Programming Tutorial - Learn the Basics of Statistical Computing (by @datalabcc and freecodecamp)
    • Learn R Programming with Johns Hopkins University (by @rdpeng)
  • Javascript
    • Learn TensorFlow.js - Deep Learning and Neural Networks with JavaScript (by @deeplizard and freecodecamp)
    • Neural Networks with JavaScript - Full Course using Brain.js (by @robertlplummer and freecodecamp)
  • Machine learning frameworks
    • TensorFlow 2.0 Complete Course (by @TechWithTimm and freecodecamp)
    • Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners (by @deeplizard and freecodecamp)
    • PyTorch for Deep Learning (by @jovianhq and freecodecamp)
    • Scikit-learn Crash Course - Machine Learning Library for Python (by @fishnets88 and freecodecamp)

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CLOUD

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Git & Github

• Github Learning Lab
  With GitHub Learning Lab, grow your skills by completing fun, realistic projects. Get advice and helpful feedback from Github's friendly Learning Lab bot.

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UI/UX

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• pathways
  develop your skills in android

• google codelabs
  guided hands-on tutorials on relating to google tools and technologies

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Competitive Programming

• Study

  • usaco.guide
  • cp-algorithms
  • geekforgeeks

• Practice

  • CodeChef
  • Codeforces
  • AtCoder
  • Topcoder
  • CSES Problemset
  • Codewars

• Books

  • Competitive Programmer's Handbook

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Miscillaneous

• code reference
  a web app with references for various languages for easy access.

• roadmap
  detailed roadmaps for software development - frontend, backend etc