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brandinho.github.io | ||
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www.arrsingh.com
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| | | | | Linear Regression predicts the value of a dependent variable (y) given one or more independent variables (x1, x2, x3...xn). In this case, y is continuous - i.e. it can hold any value. In many real world problems[1], however, we often want to predict a binary value instead | |
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dennybritz.com
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| | | | | All the code is also available as an Jupyter notebook on Github. | |
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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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ataspinar.com
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| | | In the previous blog posts we have seen how we can build Convolutional Neural Networks in Tensorflowand also how we can use Stochastic Signal Analysis techniques to classify signals and time-series. In this blog post, lets have a look and see how we can build Recurrent Neural Networks in Tensorflow and use them to classify Signals. | ||
