There are 8 repositories under artificial-neural-network topic.
A flexible artificial neural network builder to analyse performance, and optimise the best model.
2022 Coursera Machine Learning Specialization Optional Labs and Programming Assignments
Mathematics paper recapitulating the calculus behind a neural network and its back propagation
AIKA is a new type of artificial neural network designed to more closely mimic the behavior of a biological brain and to bridge the gap to classical AI. A key design decision in the Aika network is to conceptually separate the activations from their neurons, meaning that there are two separate graphs. One graph consisting of neurons and synapses representing the knowledge the network has already acquired and another graph consisting of activations and links describing the information the network was able to infer about a concrete input data set. There is a one-to-many relation between the neurons and the activations. For example, there might be a neuron representing a word or a specific meaning of a word, but there might be several activations of this neuron, each representing an occurrence of this word within the input data set. A consequence of this decision is that we have to give up on the idea of a fixed layered topology for the network, since the sequence in which the activations are fired depends on the input data set. Within the activation network, each activation is grounded within the input data set, even if there are several activations in between. This means links between activations serve two purposes. On the one hand, they are used to sum up the synapse weights and, on the other hand they propagate the identity to higher level activations.
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
Hierarchical self-organizing maps for unsupervised pattern recognition
Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)
Controllers designed to the 5MW NREL wind turbine using Simulink and Fast V8
Image Classification for Android using Artificial Neural Network using NumPy and Kivy.
:traffic_light: An Artificial Neural Network based Traffic Light Controller for intersections. Computational Intelligence class final project.
This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI
The project trains an Artificial Neural Network which can predict whether a visitor will generate revenue for the company or not.
[ICLR 2024] Dynamic Neural Response Tuning
This repository contains a gentle introduction to machine learning algorithms with hands on practical examples
An approach to tumor detection and segmentation via encoder decoder artificial neural network architecture
Very Simple and Basic Implementation of Compositional Pattern Producing Network in TensorFlow
A Multi Layer Perceptron (MLP) Artificial Neural Network (ANN) Framework Developed in C for Machine Learning (ML) and Deep Learning (DL)
Numpy实现的ANN识别手写数字mnist数据集
LoveBrains is a simulator of artificial intelligence based on a plugin system.
Self Diving Car Game using Pytorch and Kivy framework in Python
Light weight Artificial Neural Network library written in C
The code for the work presented in the research paper titled "***"
Artificial Neural Network from basic to advanced using PyTorch
C# implementation of standart deep neural network, with different types of neuro activation functions.
This repository contains a collection of machine learning and deep learning algorithms I implemented from scratch using Python and C++.
Training an Artificial Neural Network with this dataset and Predict the Diabetes.
A self-organizing feature map which is trained on a random three-dimensional (RGB) input space.
Kaggle Competition of Artificial Neural Networks and Deep Learning Course. Image Classification, Segmentation and Visual Question Answering
Personal website
This is an intelligent seat allocation system made using Flask