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blog.evjang.com | ||
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blog.otoro.net
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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 ... | |
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bdtechtalks.com
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| | | | | The transformer model has become one of the main highlights of advances in deep learning and deep neural networks. | |
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dennybritz.com
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| | | | | Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming. | |
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www.swyx.io
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| | | That one time we tried to emulate our brains with computer chips | ||
