hidden-layers

simple neural network library in ANSI C

An easy neural network for Java!

Implementation of Artificial Neural Networks using NumPy

A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.

Looking at the manifold hypothesis in deep learning. Creating a simple spiral dataset allows me to reveal how neural networks follow an optimal packing strategy during their training.

An neural network to classify the handwritten digits 0-9 for the MNIST dataset. No NN/ML libraries used.

Threat Detection System using Hybrid (Machine Learning + Lexical Analysis) learning Approach.

Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer

Genann library port to C#, simple neural network library in ANSI C

one layer and two layer neural networks

Snoop can be used to expand shortened Links such as those from bit.ly etc.to their original form without actually visting them. right from your terminal

CNN Deep Layer Filters Visualization using Tensorflow.

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.

Deep Learning projects

Deep-Learning neural network to analyze and classify the success of charitable donations.

This project is build up completely with numpy. It implements basic neural network concepts including backpropagation, hidden layers, activation function and gradient descent.

Deep Neural Network Classifier for the Win/Linux/OSX platform based on the GTK# Framework

Implementing a 2-class classification neural network with a single hidden layer. Using units with a non-linear activation function such as tanh. Computing the cross entropy loss. Implementing forward and backward propagation.