Here is a listing of all the tutorials on this AI Shack
Tracks are a series of tutorials put together in a logical order
Figure out how some of the basic algorithms in computer vision work. This track takes you through a handful of everyday use algorithms.
Learn how commonly used algorithms in computer vision work under the hood. You'll learn a wide variety of techniques to add to your arsenal.
Learn the fundamentals of OpenCV and get kick-started with computer vision.
Some broad categories of topics covered on AI Shack. Pick one to drill down.
Core concepts in image processing and computer vision are covered here. Things like convolutions, hough transforms, camera calibration are here! Most of these are programming agnostic - however, I've mostly used OpenCV to implement these ideas.
Occasionally I write about electronics, microcontrollers and Raspberry Pis. These tutorials are somehow related to AI - but focus more on the electronics aspect.
Things that don't fit anywhere else go here!
SVMs, neural networks, k-means and any related machine learning techniques that can help augment your AI journey!
Neural networks have gotten extremely useful lately and this section describes how to use them in your own attempts at understanding the world.
Ideas or concepts focusing primarily on OpenCV go here. It might be something idiosyncratic to OpenCV (like cv::Mat) or a useful tip. Things like that go here!
Long form articles that take an idea and build them from starting to the end. These are very insightful and help understand the mathematical mumbo-jumbo with a real-life use-case!
My take on things I've used personally and I endorse. Articles here include books, software, etc.
These articles are a bit more focused on robotics. Things like competitive robotics, industrial robotics, etc go here. Self-driven cars belong here as well!
Learn about the latest in AI technology with in-depth tutorials on vision and learning!
Created by Utkarsh Sinha