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 jaykmody.com
An Intuition for Attention | Jay Mody
| | marcospereira.me
Backpropagation From Scratch-Marcos Pereira
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| | In this post we summarize the math behind deep learning and implement a simple network that achieves 85% accuracy classifying digits from the MNIST dataset.
| | tomhazledine.com
How does cosine similarity work?
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| | When working with LLM embeddings, it is often important to be able to compare them. Cosine similarity is the recommended way to do this.
| | sebastianraschka.com
Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch
2.4 parsecs away

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| | I'm Sebastian: a machine learning & AI researcher, programmer, and author. As Staff Research Engineer Lightning AI, I focus on the intersection of AI research, software development, and large language models (LLMs).
| | blog.otoro.net
Neural Network Evolution Playground with Backprop NEAT |
9.9 parsecs away

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| [AI summary] This article describes a project that combines genetic algorithms, NEAT (NeuroEvolution of Augmenting Topologies), and backpropagation to evolve neural networks for classification tasks. The key components include: 1) Using NEAT to evolve neural networks with various activation functions, 2) Applying backpropagation to optimize the weights of these networks, and 3) Visualizing the results of the evolved networks on different datasets (e.g., XOR, two circles, spiral). The project also includes a web-based demo where users can interact with the system, adjust parameters, and observe the evolution process. The author explores how the genetic algorithm can discover useful features (like squaring inputs) without human intervention, and discusses the ...