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ML and robotics notes

Tutorials and implementations of machine learning and robotics algorithms.

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Intuitively Understanding Harris Corner Detector

If you ever tried to learn how the Harris corner detection algorithm works, you might have noticed that the process is not intuitive at all. First, you start with an energy function, approximate it using Taylor approximation, get a matrix from that, then find the eigenvalues of that matrix, etc. But when you come to the final implementation, it is rather simple and seems easier. If you are like…

Step-by-Step Guide to Image Classification with Vision Transformers (ViT)

In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture.

Transformers Unfolded: A Layered Approach to Implementation

In this tutorial, we will implement transformers step-by-step and understand their implementation. There are other great tutorials on the implementation of transformers, but they usually dive into the complex parts too early, like they directly start implementing additional parts like masks and multi-head attention, but it is not very intuitional without first building the core part of the…

Understanding and Building Neural Networks: A Step-by-Step Guide from Scratch

In this tutorial, we will learn two different methods to implement neural networks from scratch using Python: Extremely simple method: Finite difference Still a very simple method: Backpropagation