There are 2 repositories under artifical-neural-network topic.
ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance
Awesome tutorials, papers, projects and tools for Reservoir Computing techniques like Echo State Networks (ESN).
Huge-scale, high-performance flow cytometry clustering in Julia
Option pricing and Delta hedging performance comparison between Black and Scholes vs Artificial Neural Network
Case Studies and Projects in Machine Learning/EDA/DL
Recognize handwritten digits using back-propagation algorithm on MNIST data-set
(Machine) Learning to Do More with Less
The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.
A project to filter SQL Injection and XSS attacks using ANN -- in Ruby
Fruit Classifier with ANN
Innervator: Hardware Acceleration for Artificial Neural Networks in FPGA using VHDL.
Performed data analysis with tensorflow and keras.
A Machine Learning library for Neural Networks fully written in python. It supports multiple layers of neurons and offers a variety of activation functions, optimization algorithms, and utility functions.
ANN detecting signal from internal variability
Yapay Zeka dersinde yapılan Yapay Sinir Ağları konusunda gerekli hesaplamaları verilen giriş ve ağırlıklara göre hesaplayan program.
artifical neural network (ann) supervised learning javascript library and 2d game example
Breast cancer prediction🎗️using logistic regression, random forest and artificial neural network
Implementation of algorithms for soft computing
ANN model which identifies why a customer is churning from a bank
IST 5535 Machine Learning Algorithms and Applications in R Project, where we developed a predictive model to predict the UPDRS score for Parkinsons Disease based on different dysphonia (noise) measures.
This predicts the future energy demand by using a LSTM (Long Short Term Memory) Model i.e. (a kind of Recurrent Neural Network) based only on time series(sequence-to-sequence).
The purpose of this study is to recognize the numbers drawn by human on computer. For the solution to succeed of this problem used artificial neural networks. Artificial neural Networks is considered a good method these days for estimation, recognition and classification etc. problems. Tensorflow library is used for the development of the application in this study. Tensorflow Library contains the methods required for artificial intelligence, machine learning, deep learning
Projects: Genetic Algorithms (GA) for cryptarithmetic problems , Artifical Neural Network (ANN) for recognize some digits, Ant Colony Optimization (ACO) for resolve Travel Salesman Problem (TSP).
Hecho con la tecnología de Windows Forms en el lenguaje C#. Un perceptrón simple que simula resultados mediante entradas
This project uses MNIST data set and uses artificial neural network to recognize hand written digits, this project uses tensor flow as backend and keras as frontend
This project made with MATLAB. It's about machine learning. Artificial Neural Network in the form of Multilayer Perceptron.
Research for justifying the problem domain for sound recognition with neural network applying both ANN and CNN with the beginning of poster presentation on Genetic algorithm for Prediction of Pathological Subjects
This repository contains projects i completed throughout the "Machine Learning and Deep Learning Projects in Python" course by S. Emadedin Hashemi on Udemy
Using Hopfield Neural Networks to recognise digits 0 - 9. Testing the Hebbian Training Method vs the Storkey Training Method.
In this project, I used the RAVDESS dataset with eight emotions, each at two intensities. I built a model extracting five features from speech signals to classify emotions, providing valuable insights.