GitHub topics: exploding-gradient
Hasnat-Aarif-Aslam/How-to-Improve-the-Performance-of-a-Neural-Network
This pdf shows some methods to fine tune the hyperparameters of a Neural Network to increase it's performance. It also puts light on some of the common problems related to Neural Networks along with their solutions.
Language: Jupyter Notebook - Size: 25.2 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

EmamulHossen/Gradient-Problem-in-RNN
The vanishing gradient problem is a well-known issue in training recurrent neural networks (RNNs). It occurs when gradients (derivatives of the loss with respect to the network's parameters) become too small as they are backpropagated through the network during training.
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hwixley/MLP-coursework2-report
Machine Learning Practical - Coursework 2 Report: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.
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hwixley/MLP-coursework2
Machine Learning Practical - Coursework 2: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.
Language: Python - Size: 3.37 GB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

fabiogaiera/machine-learning-glossary
Machine Learning Concepts
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Dev-Aligator/Recurrent-Neural-Networks-RNNs-
First public project written in Python i guess, anyway this is a repository for my class CS115.N12.KHCL
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