hidden-layers
There are 58 repositories under hidden-layers topic.
codeplea/genann
simple neural network library in ANSI C
goessl/MachineLearning
An easy neural network for Java!
ahmedfgad/NumPyANN
Implementation of Artificial Neural Networks using NumPy
rtflynn/Cifar-Autoencoder
A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
Ranlot/spiralNet
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.
XAheli/Predicting-Indian-Stocks-Price-with-Stacked-LSTM
Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.
nathansamsel/mnist_neural_network
An neural network to classify the handwritten digits 0-9 for the MNIST dataset. No NN/ML libraries used.
anubhavsaxena14/Threat-Detection-using-Sentiment-Analysis
Threat Detection System using Hybrid (Machine Learning + Lexical Analysis) learning Approach.
LanzaSchneider/GenannSharp
Genann library port to C#, simple neural network library in ANSI C
Ishan7390/NN_fashMNIST
Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer
hknakst/artificial-neural-networks-YapaySinirAglari-
one layer and two layer neural networks
vrikodar/Snoop
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
anujdutt9/CNN-Deep-Layer-Filters-Visualization
CNN Deep Layer Filters Visualization using Tensorflow.
Ashwanikumarkashyap/neural-net-breast-cancer-prediction-from-scratch
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.
chiapeilin/Neural-Network
The code of forward propagation , cost function , backpropagation and visualize the hidden layer.
daelsepara/DeepNeuralNetworkClassifier
Deep Neural Network Classifier for the Win/Linux/OSX platform based on the GTK# Framework
HarveyBrezinaConniffe/MNIST-NeuralNet
A implementation of a Neural Network in vanilla python that trains on the MNIST handwritten digit classifiction problem.
JLeigh101/deep-learning-challenge
NU Bootcamp Module 21
Karla-Flores/Neural-Network--Charity-Donation
Deep-Learning neural network to analyze and classify the success of charitable donations.
nikhildagarwal/Number_Classifier_ML
Python neural network built from scratch. Uses Machine Learning algorithms to correctly classify handwritten numbers into digits.
Pegah-Ardehkhani/One-Hidden-Layer-Neural-Network-From-Scratch
"One Hidden Layer Neural Network" from Scratch
rajeshidumalla/Classification-with-one-hidden-layer
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.
ramapitecusment/student_academic_performance
Prediction of Students' Academic Performance Dataset: Cart Trees, Random Forest, Cross Validation and Neuralnet
Satyaki0924/bike-sharing-prediction-with-neural-network
This project is build up completely with numpy. It implements basic neural network concepts including backpropagation, hidden layers, activation function and gradient descent.
zenetio/Neural-Networks-and-Deep-Learning
Deep Learning projects
Annbelbella/Deep_Learning_Challenge
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
Hamim-Hussain/Enhancing-Deep-Learning-Model-Performance
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. Using 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 if funded.
LanzaSchneider/GenannSharpUnsafe
Genann library port to C# (unsafe version), simple neural network library
openworld42/Backpropagation
Neural backpropagation with examples and training (Java)
soheilabadifard/Neural_Network_Regressor
Neural Networks scratch
Suvodeep-Das/Deep-Learning
This repository covers the practical applications of Deep Learning
Pegah-Ardehkhani/Deep-Neural-Network-From-Scratch
"Deep Neural Network" from Scratch
RJBarker/deep-learning-challenge
Create a neural network through TensorFlow and Keras to build a model which has the ability to assess an organisation's ability to be successful with funding from the Alphabet Soup charity
Tekateka/Neural_Network_Charity_Analysis
Compiled, trained, evaluated, and optimized models using Neural Networks and Deep Learning Models.