Deep Learning with Exponential Linear Units (ELUs) activation function
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Updated
Feb 18, 2018 - Python
Deep Learning with Exponential Linear Units (ELUs) activation function
Project Regarding Analysis and Implementation of https://arxiv.org/abs/1602.02068
The Deep Learning exercises provided in DataCamp
Graduated optimization on neural networks via adjustment of activation functions
[TCAD 2018] Code for “Design Space Exploration of Neural Network Activation Function Circuits”
Feed Forward Neural Network to classify the FB post likes in classes of low likes or moderate likes or high likes, back propagtion is implemented with decay learning rate method
A Basic Introduction To Neural Networks: Machine Being Human!
Visualizations of various activation functions for neural networks in TensorFlow
Bionodal Root Unit (BRU) implemented with Chainer-v5
Sıfırdan python ile yapay sinir ağı kütüphanesi geliştirme
to maintain activation functions used in machine learning
Multilayer neural network framework implementation, used for classification and regression task. Can use multiple activation functions with backpropagation based on autograd library. Contains polynomial activation function for regression task.
Application of LSTM networks and modified RNN cells to various Time Series Classification problems
ML algorithms implemented in Python
Korean OCR Model Design(한글 OCR 모델 설계)
A PyTorch implementation of funnel activation https://arxiv.org/pdf/2007.11824.pdf
This Project is based on Neural Network to classify between Dogs and Cats.
This project proposes a neural network architecture Residual Dense Neural Network - ResDen, to dig the optimization ability of neural networks. With enhanced modeling of Resnet and Densenet, this architecture is easier to interpret and less prone to overfitting than traditional fully connected layers or even architectures such as Resnet with hig…
3D visualization of common activation functions
A feedforward neural network to predict wine quality based on a number of scientific factors. NOTE: This is purely an educational project. This is neither an efficient nor realistic neural network for commercial use.
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