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brandinho.github.io | ||
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www.paepper.com
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| | | | | [AI summary] This article explains how to train a simple neural network using Numpy in Python without relying on frameworks like TensorFlow or PyTorch, focusing on the implementation of ReLU activation, weight initialization, and gradient descent for optimization. | |
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erikbern.com
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| | | | | I've been spending quite some time lately playing around with RNN's for collaborative filtering. RNN's are models that predict a sequence of something. The beauty is that this something can be anything really - as long as you can design an output gate with a proper loss function, you can model essentially anything. | |
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www.khanna.law
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| | | | | You want to train a deep neural network. You have the data. It's labeled and wrangled into a useful format. What do you do now? | |
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thecodebarbarian.com
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| | | [AI summary] The article discusses building a neural network using Brain.js to predict wine quality ratings based on chemical properties, including data preprocessing, training, and evaluation. | ||
