There are 2 repositories under feed-forward-neural-networks topic.
Official project website for the CVPR 2020 paper (Oral Presentation) "Cascaded deep monocular 3D human pose estimation wth evolutionary training data"
A Fortran-based feed-forward neural network library. Whilst this library currently has a focus on 3D convolutional neural networks (CNNs), it can handle most standard hidden layer forms of neural networks, with the plan to integrate more.
reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization
Evolutionary Computation Framework in Java
This repository contains materials and course projects during attending the Intelligent Systems Course, for more detailed information please have a look at my Final_Report files which have been separately uploaded for each of the projects and consist of all required information about the implementations, analyses, and anything else you may concern about that!
Infer cell-cell communications based on feed-forward neural network
This repository hosts the programming exercises for the course "Machine Learning" of AUEB Informatics.
🤖 Query local AI for quick answers and explanations with this simple CLI tool, built using V.
A Repo for Neural Network Assignment
Sentiment Classifier using: Softmax-Regression, Feed-Forward Neural Network, Bidirectional stacked LSTM/GRU Recursive Neural Network, fine-tuning on BERT pre-trained model. Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)
A Feed-forward Neural Network model in JAVA for Intelligent Character Recognition - trained and tested on the MNIST dataset. Classification accuracy up to 98.22%.
🤖 Artificial intelligence (neural network) proof of concept to solve the classic XOR problem. It uses known concepts to solve problems in neural networks, such as Gradient Descent, Feed Forward and Back Propagation.
Deep Learning image recognition with TensorFlow Keras. Created a Feed-Forward-Network from scratch and used pretrained networks MobileNetV2, ResNet50, and VGG16.
A simple sentiment analyser
A Novel Approach to Noise Generation using a Feed Forward Seed Based Noise algorithm
Repository for Project 2 in FYS-STK4155
a vectorized, python-based implementation of deep feed forward neural network for binary classification.
An AI-powered Flappy Bird game where a neural network learns to play the game using the NEAT (NeuroEvolution of Augmenting Topologies) algorithm. This project demonstrates neuroevolution in action by evolving bird agents that improve over generations without human input.
Using a deep neural network to predict the outcome of a statistic-based combat system
Machine learning algorithms for the calibration of epidemiological compartmental models: application to the Italian COVID-19 outbreaks in Italy and to the newly developed SUIHTER model.
A Physics-Informed Neural Network (PINN) implemented in PyTorch to solve the N-dimensional coupled spring-mass system ODEs.
neural network from scratch. ive implemented backpropagation from scratch using micrograd, which i build by scratch using karpathy's guide. also has optimizer, and coded a little one some manual approached to optimize using randomizing weights and biases.
Breast ultrasound image classification with Feed Forward Neural Network and PyTorch
Python-based implementation of different deep learning projects.
Prediction of Protein-Protein Interaction (PPI) sites for the classification of aminoacidic interaction
This project was completed during the completion of the Master of Science degree in Data Analytics from Western Governors University
This repository contains codebase for a basic Feed Forward Network in tensorflow without using keras that operates in a continual learning setting
Feed Forward Neural Network (Regression)
Straight-forward DL Pet projects
Feed foward function approximation using a neural network
Tugas Besar Machine Learning Bagian A
Tugas besar pembelajaran mesin mini batch gradient descent
PyTorch Workflow Examples of Foundations & Architectures, Training & Robustness, and Advanced & Production Readiness.