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www.paepper.com | ||
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towardsdatascience.com
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| | | | | Learn how to build feedforward neural networks that are interpretable by design using PyTorch. | |
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coen.needell.org
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| | | | | In my last post on computer vision and memorability, I looked at an already existing model and started experimenting with variations on that architecture. The most successful attempts were those that use Residual Neural Networks. These are a type of deep neural network built to mimic specific visual structures in the brain. ResMem, one of the new models, uses a variation on ResNet in its architecture to leverage that optical identification power towards memorability estimation. M3M, another new model, ex... | |
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sebastianraschka.com
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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). | |
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www.v7labs.com
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| | | Recurrent neural networks (RNNs) are well-suited for processing sequences of data. Explore different types of RNNs and how they work. | ||
