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Structuring Deep Learning Projects
| | programmathically.com
Understanding The Exploding and Vanishing Gradients Problem - Programmathically
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| | Sharing is caringTweetIn this post, we develop an understanding of why gradients can vanish or explode when training deep neural networks. Furthermore, we look at some strategies for avoiding exploding and vanishing gradients. The vanishing gradient problem describes a situation encountered in the training of neural networks where the gradients used to update the weights []
| | blog.ephorie.de
Logistic Regression as the Smallest Possible Neural Network - Learning Machines
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| | www.v7labs.com
Activation Functions in Neural Networks [12 Types & Use Cases]
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| | A neural network activation function is a function that is applied to the output of a neuron. Learn about different types of activation functions and how they work.
| | aimatters.wordpress.com
Solving MNIST with a Neural Network from the ground up - On Machine Intelligence
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| Note: Here's the Python source code for this project in a Jupyter notebook on GitHub I've written before about the benefits of reinventing the wheel and this is one of those occasions where it was definitely worth the effort. Sometimes, there is just no substitute for trying to implement an algorithm to really understand what's...