ML Engineering Interview Challenges 🚀💻

Welcome to the ML Engineering Challenges repository! 🎉 This repo will have 50 challenges ranging from Easy to Hard that are designed to help you sharpen ML engineering skills.

(Many of these challenges have been designed with a Computer Vision engineer in mind as I've found it hard to find targeted resources, however, many of the challenges are transferrable!)

What's Inside? 📂

• Levels of Difficulty:
  • Easy🏃‍♂️
  • Medium💡
  • Hard🚀
• Contents: (filling as I write the solutions):
  • 🚀Batch Normalisation from Scratch: Problem Solution
  • 🏃‍♂️Simple Image Data Augmentation Pipeline: Problem Solution
  • 💡Optimise Image Processing with Vectorisation: Problem Solution
  • 💡PyTorch Training Loop from Scratch: Problem Solution
  • 💡2D Convolution from Scratch using Numpy
    • No padding, dilation or stride: Problem Solution
    • [Only padding]
    • [Padding, stride & dilation]
• Hands-On Python Code: Each challenge comes with scaffold code to get started. This can be found in the 'Problems' folder and solutions in the 'Solutions' folder 🐍
• Solutions: Every solution is my own and if you have a better approach, please share 👩🏽‍💻

Love or Hate? 🤔

• Take a minute and share your thoughts (anonymously) so I can make this page better 🫶🏽 : https://forms.gle/M79XckyHAUK1qD2d6
• I will implement as many changes as I can!

How to Get Started 🚀

1. Clone the Repo:

   git clone https://github.com/sriyaroy/coding-challenges.git
   cd coding-challenges