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blog.evjang.com | ||
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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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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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www.machinedlearnings.com
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| | | | | Rather than a laundry list of papers, I thought I would comment on some trends that I observed at NIPS this year. Deep Learning is Back Fo... | |
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blog.paperspace.com
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| | | Follow this tutorial to learn what attention in deep learning is, and why attention is so important in image classification tasks. We then follow up with a demo on implementing attention from scratch with VGG. | ||
