epochs
There are 43 repositories under epochs topic.
JuliaSpaceMissionDesign/Tempo.jl
Efficient Astronomical Time transformations in Julia.
DouweHorsthuis/EEG_to_ERP_pipeline_stats_R
General pipeline used for analyzing EEG data where Raw EEG data gets transformed into ERPS and Stats are done in R (Mixed effects models)
Data-Science-Community-SRM/Hand-Gesture-Recognition-Rock-Paper-Scissor
Hand Gesture Recognition and Modification was based on transfer learning Inception v3 model using Keras with Tensorflow backend trained on 4 classes - rock, paper, scissors, and nothing hand signs. The final trained model resulted in an accuracy of 97.05%. The model was deployed using Streamlit on Heroku Paas.
gabrieldim/Baby-Health-Data-Science
Baby Health model made in Python.
persistenceOne/persistence-sdk
Node modules and client utilities to build Persistence platform node applications.
MoinDalvs/Neural_Networks_Forest_Fire_Classification
PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
krishnadevz/image-classification-and-manipulation-in-python-machine-learning
image classification and manipulation in python machine learning on fashion mnist dataset
Scorepochs-tools/scorepochs_py
scorEpochs: a computer aided scoring tool for resting-state M/EEG epochs
ahtolee/GazeBasedEpochSelection
Gaze data -based epoch selection algorithm for eye tracker assisted visual evoked potential paradigm
fitushar/Cyclical-Learning-Rates-for-Training-Neural-Networks-With-Unbalanced-Data-Sets
As the learning rate is one of the most important hyper-parameters to tune for training convolutional neural networks. In this paper, a powerful technique to select a range of learning rates for a neural network that named cyclical learning rate was implemented with two different skewness degrees. It is an approach to adjust where the value is cycled between a lower bound and upper bound. CLR policies are computationally simpler and can avoid the computational expense of fine tuning with fixed learning rate. It is clearly shown that changing the learning rate during the training phase provides by far better results than fixed values with similar or even smaller number of epochs.
Ali-jalil88/glass-classification-DL-ANN
Glass Classification using Deep Learning Model ANN
Aypak/tf_gan_handwritten_digits
A Generative Adversarial Network (GAN) that generates handwritten digits(0 to 9). Uses mnist dataset. Written in R
jmarihawkins/Employee-Attrition-and-Department-Prediction
The purpose of this project is to develop a machine learning model that predicts employee attrition (whether an employee will leave the company) and department assignment (which department an employee belongs to) based on various factors. These factors include age, travel frequency, education level, job satisfaction, marital status, and more.
TrentBrunson/Neural_Networks
TensorFlow 2.2, Keras, Deep Learning
Waking-Dreamer/Investment_Predictions_Deep_Learning
This project creates a machine learning model that predicts the success of investing in a business venture.
38832/potato_disease
A TensorFlow-based project for classifying images with a CNN. Includes data preprocessing, model training, evaluation, and visualization of results.
AdityaKuchulakanti/NeuralNetwork_Projects
NN project to understand from scratch how internally Weights are applied, Epochs, Backpropagation, Error calculation, Gradient.
anjanchowdhury/Image-Caption-Generator
Image caption generator project is automatically describes images with coherent and relevant textual captions.
Anne-Andresen/EEG-processing
EEG data collection and processing in matlab. Proposed data collection algorithm and Processing pipeline for evoked potentials of EEG signals or regular EEG signals. Furthermore
elmahsieh/LogisticRegressionTraining
This project involves training a machine learning model and plotting its learning curves to analyze training and testing accuracies, utilizing Java for model execution and Python for data visualization. It includes commands for compiling and running the Java program, generating plots, and sending results via email.
LucaGatt22/MLP-neural-network
A Multi Layer Perceptron created to calculate XOR (eXclusive OR) on 5 inputs
mivinmathew/CNNImageClassifier
Using Convolutional Neural Networks to create image classifiers [ cats + dogs & cats + dogs + lions + tigers ]
saikrishnabudi/Artificial-Neural-Network
Artificial Neural Network using PyTorch & Keras Libraries
Scorepochs-tools/Scorepochs-tools
Scorepochs: a computer aided scoring tool for resting-state M/EEG epochs
Scorepochs-tools/scorepochs_mat
Scorepochs: a computer aided scoring tool for resting-state M/EEG epochs
shoaib1522/Credit-Card-Fraud-Analysis
"A comprehensive project on Credit Card Fraud Detection combining Exploratory Data Analysis, Machine Learning, and an interactive Streamlit web app for real-world applicability."
abidor13/Neural_Network_Charity_Analysis
Neural_Network_Charity_Analysis
ajaybiswas22/Neural-Network-Logic-Gates
This repository provides the Implementation of logic gates using neural networks.
chandnii7/Convolutional-Neural-Network
Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
Ishan-Kotian/Nerual-Network_Image-Data
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. Neural networks can adapt to changing input; so the network generates the best possible result without needing to redesign the output criteria.
kavilivishnu/Image_classification_using_the_CIFAR_10_dataset
The main concentration of this project lies on image calssification using traditional CNN(Convolution Neural Networks), and also a couple of "BASE MODELS" such as "RestNet50", "DenseNet121" and "EfficientNetB0" that upgraded the performance of our CNN, followed by the Fully Connected NN, that we are using to train our model on.
manishthilagar/Estimating-evoked-responses-of-EEG-using-MNE-python
Estimating evoked responses
mychele-larson/Deep_Learning_Challenge
Module 21 Challenge
npantfoerder/neural-network-charity-analysis
Designing a deep learning neural network with TensorFlow to predict the success of donations
saikrishnabudi/PyTorch-ANN-Model
PyTorch Library on Artificial Neural Network Model
smykes/geo-time-scale-lambda
A tool to print the eon, era, period, epoch, and age of a given positive whole number.