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 www.lesswrong.com
Nonlinear limitations of ReLUs - LessWrong
| | michael-lewis.com
A machine learning glossary for hackers · Michael I Lewis
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| | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background.
| | adl1995.github.io
An overview of activation functions used in neural networks
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| | [AI summary] The article explains various activation functions used in neural networks, their properties, and applications, including binary step, tanh, ReLU, and softmax functions.
| | www.paepper.com
Training a neural network with Numpy :: Päpper's Machine Learning Blog - This blog features state of the art applications in ...
3.1 parsecs away

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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.
| | golb.hplar.ch
Building a simple neural network with Java and JavaScript
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| [AI summary] The blog post details the author's experience implementing a feedforward neural network for digit recognition using Java and JavaScript, explaining the underlying algorithms, shared external libraries, and architectural decisions while reviewing an introductory book on the topic.