activation-functions

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Here are 177 public repositories matching this topic...

freeknortier / Activation-Functions-Visualizations

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Visualizations of various activation functions for neural networks in TensorFlow

machine-learning tensorflow activation-functions

Updated Feb 26, 2019
Python

arbiter1elegantiae / kaf-nets

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Kernel-Based Activation Functions implementation and experiments

kernel deep-learning neural-networks cifar10 susy activation-functions kaf-nets

Updated Jul 25, 2020
Jupyter Notebook

vtramo / neural-networks-experiments-from-scratch

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The objective of this repository is to provide a learning and experimentation environment to better understand the details and fundamental concepts of neural networks by building neural networks from scratch.

Updated Jul 22, 2023
Python

arkanivasarkar / Deep-Learning-from-Scratch

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Implementation of a Fully Connected Neural Network, Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) from Scratch, using NumPy.

deep-learning neural-network numpy optimizer cnn dropout rnn feedforward-neural-network pooling batchnorm university-assignment oops-in-python cross-entropy-loss activation-functions neural-networks-from-scratch

Updated May 20, 2023
Python

Vercaca / activation_functions

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to maintain activation functions used in machine learning

machine-learning sigmoid activation-functions sign-functions

Updated Apr 17, 2019
Python

op12no2 / toynet

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A Javascript version of Alexander Schiendorfer's blog post "A worked example of backpropagation".

javascript machine-learning neural-network backpropagation activation-functions mini-batching

Updated Jul 9, 2021
JavaScript

TanishaCooper / deep_learning_charity_funding-_predictor

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The nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures. With your knowledge of machine learning and neural networks, you’ll use the features in the provided dataset to create a binary classifier that can predict whether applicants will be successful…

python deep-neural-networks deep-learning neural-network pandas-dataframe jupyter-notebook activation-functions

Updated Aug 19, 2022
Jupyter Notebook

dansolombrino / CreActive

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A set of experiments on Deep Neural Networks activation functions

deep-neural-networks deep-learning nonlinear-optimization activation-functions

Updated May 10, 2023
Python

basthel / Visualization_NB

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Jupyter Notebooks for Visualization

visualization cnn activation-functions optimizer-visualization

Updated May 28, 2018
Jupyter Notebook

disha-1994 / RC2020

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Reproducibility Challenge 2020 papers

computer-vision deep-learning optimization pytorch convolutional-neural-networks attention-mechanism activation-functions reproducibility-challenge

Updated Feb 28, 2021
Python

p-dirac / javafx-convolution-network

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JavaFx Application for Convolutional Network to perfom Image Classification using Softmax Output Layer, Back Propagation, Gradient Descent, Partial Derivatives, Matrix Flattening, Matrix Unfolding, Concurrent Task, Performance Histogram, Confusion Matrix

javafx convolutional-layers image-classification convolution performance-visualization convolutional-networks javafx-application gradient-descent convolutional-neural-network backpropagation maxpooling unfolding matrix-library concurrent-tasks activation-functions partial-derivatives softmax-function matrix-flattening matrix-unfolding

Updated Jun 8, 2023
Java

atul04 / Feed-Forward-Neural-Network-Based-Classifier-Facebook-Post

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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

Updated Nov 6, 2018
Python

nauman-akram / NeuralNets-Implementation

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Bunch of neural nets implemented from scratch for learning purposes

machine-learning deep-learning linear-regression regression cnn lstm mnist neural-networks classification logistic-regression cifar10 activation-functions

Updated Aug 12, 2020
Jupyter Notebook

shen3443 / wine-quality-dataset-vanilla-python-ML

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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.

python machine-learning neural-network ml feedforward-neural-network from-scratch loss-functions wine-quality educational-project activation-functions