Implementing multilayer neural networks through backpropagation using Java.
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Updated
Mar 13, 2017 - Java
Implementing multilayer neural networks through backpropagation using Java.
A tiny deep learning library written in Java
A short tutorial to learn the backpropagation technique in Neural Networks by implementing the algorithm from scratch in Java. Includes source code.
A simple Java AI library for personal use.
Flappy Bird for artificial intelligence/machine learning (Agent available: Q-Learning, SARSA, and combined with Backpropagation)
neural network
Speech Recognition experiment using MFCC Feature Extraction + Feed Forward Neural Network (training with Backpropagation)
A fully functioning neural network made from scratch in Java without the use of any external libraries. Comes with extended functionality such as L2 regularization, Mini-batch gradient descent, variable activation functions, etc. Fully commented for ease of understanding! Now imported to IntelliJ.
A deep learning library developed from scratch in Java.
Easy to use neural network library in java
Conjunto de ferramentas para lidar com treinamentos de redes neurais artificiais
A simple self learning Neural Network that can detect/learn alot of things, highly scalable. Made in Java
Deep Learning library.
Neural Networks implemented in Java
Lightweighted NeuralNetwork Framework
Implementation of an ANN for recognisement of the Iris plant-family
Homework Assignments for CS 540 - Artificial Intelligence at UW Madison
An object oriented neural network library.
Implementation of an ANN for recognisement of the specialization fields at ESPM Information Systems (TECH) students
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