Implementation of CORDIC Algorithms Using Verilog

Deep Learning

Simple multi layer perceptron application using feed forward back propagation algorithm

A data classification using MLP

Classes Angle, GeoPos, UTM32 and some other Math functions

Faster Java implementations of hypot, expm1, cos, sinh, cosh, tanh, asin, acos, atan and atan2

A neural network (NN) having two hidden layers is implemented, besides the input and output layers. The code gives choise to the user to use sigmoid, tanh orrelu as the activation function. Prediction accuracy is computed at the end.

Implementation of an ANN for recognisement of the Iris plant-family

"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "

Neural Network from scratch without any machine learning libraries

Artificial Neural Networks Activation Functions

Modifies a neural network's hyperparameters, activation functions, cost functions, and regularization methods to improve training performance and generalization.

GAAF implementation on Keras

Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.

Lightweight neural network library written in ANSI-C supporting prediction and backpropagation for Convolutional- and Fully Connected neural networks

Compute the hyperbolic tangent of a number.

Neural network with 2 hidden layers

Create an iterator which evaluates the hyperbolic tangent for each iterated value.

Compute the hyperbolic cotangent of a number.