tanh

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hasanur-rahman / AI-Scratch-Projects

I have implemented some AI projects from scratch implementation without explicit use of the built-in-libraries and thus added to this repo.

neural-network python3 image-classification logistic-regression binary-classification tanh sigmoid-function scratch-implementation backward-propagation forward-propagation planar-classifier

Updated Aug 6, 2020
Jupyter Notebook

mmcdan13 / Neural_Network_Charity_Analysis

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Deep Learning model for predicting success after donation coded in Google Colab

python deep-neural-networks deep-learning tanh googlecolab googlecolaboratory

Updated Oct 10, 2022
Jupyter Notebook

rishav08 / 1layer_2layer_4layer_NN

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Developed Neural Network (NN) having one hidden layer, two hidden layers and four hidden layers, besides the input and output layers. Tested with Sigmoid, tanh and ReLu activation function. Used Scikit learn for pre-processing data.

scikit-learn machine-learning-algorithms python3 neural-networks sigmoid tanh relu

Updated Mar 19, 2018
Python

Gaurav-Van / CNN-from-scratch

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Revising concepts of CNN by building them from scratch using NumPy.

deep-learning neural-networks mnist-dataset artificial-neural-networks convolution scratch convolutional-neural-networks tanh sigmoid-function partial-derivatives cross-correlations convolution-neural-networks-from-scratch

Updated Oct 11, 2024
Python

peter-strom / ML-p2-Neural_net_embedded

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raspberry-pi embedded neural-network embedded-systems artificial-neural-network backpropagation feedforward tanh relu gpiod

Updated Feb 1, 2023
C++

imane-ayouni / Electricity-Production-Forecast-using-RNN-and-LSTM

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Time series forecast using RNN and LSTM

time-series forecast lstm-model tanh rnn-pytorch

Updated Aug 28, 2023
Jupyter Notebook

dserbano / machine_learning_smartnet_2

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2nd Project of Course 'Machine Learning' of the SMARTNET programme. Taken at the National and Kapodistrian University of Athens.

python machine-learning dropout neural-networks classification convolutional-neural-networks support-vector-machines multi-label-classification convolutional radial-basis-function backpropagation-algorithm softmax tanh pooling sigmoid-function relu digit-classifier lecun

Updated Feb 28, 2020
Python

IlkayAtes11 / Alphabet_Soup_Charity_Application_Deep_Learning_Model

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deep-learning tensorflow sklearn pandas neural-networks keras-neural-networks sigmoid tanh relu googlecolab keras-tuner

Updated Mar 21, 2023
Jupyter Notebook

freire-guido / learnball

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Exploration of teamwork in neural networks

javascript machine-learning reinforcement-learning neural-network soccer tanh

Updated Apr 30, 2023
JavaScript

kopalgarg / GAN-keras

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implementing DCGANs using keras

tanh relu

Updated Jan 31, 2022
Jupyter Notebook

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

dhawal777 / Neural-Network

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Neural Network implementation from scratch along with its analysis with different type of activation function and with variation in hidden layer size and depth.

neural-network jupyter-notebook matplotlib tanh sigmoid-function relu

Updated Mar 28, 2019
Jupyter Notebook

sanjeewa999 / Activation-functions-in-Neural-Networks

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An activation function in the context of neural networks is a mathematical function applied to the output of a neuron. The purpose of an activation function is to introduce non-linearity into the model, allowing the network to learn and represent complex patterns in the data.

machine-learning neural-networks sigmoid tanh relu activation-functions leaked-relu