sigmoid

EN10/CIFAR

CIFAR 10 image dataset

11fenil11/Covid19-Detection-Using-Chest-X-Ray

Covid-19 detection in chest x-ray images using Convolution Neural Network.

EPSOFT/Deep-Learning

Deep Learning

zoziha/auto-diff

Fortran backward (reverse) mode automatic differentiation.

KhaledAshrafH/Logistic-Regression

This program implements logistic regression from scratch using the gradient descent algorithm in Python to predict whether customers will purchase a new car based on their age and salary.

YeongHyeon/Compare_Activation_Function

Compare vanishing gradient problem case by case.

aysebilgegunduz/FeedFwBackProp

Simple multi layer perceptron application using feed forward back propagation algorithm

ChriZ982/NeuralNetTest

Test project for neural networks - Handwritten digit recognition on MNIST dataset

VCHui/xor_pytorch

A classical XOR neural network using pytorch

Ashwanikumarkashyap/neural-net-breast-cancer-prediction-from-scratch

A neural network (NN) having two hidden layers is implemented, besides the input and output layers. The code gives choise to the user to use sigmoid, tanh orrelu as the activation function. Prediction accuracy is computed at the end.

hamk3010/Tweet-Classifier

A repository with Twitter data and tweet classifiers using several machine learning approaches to measure the accuracy and performance of the approaches on classifying tweets.🐧

anshul1004/NeuralNetwork

Neural Network from scratch without any machine learning libraries

Ashot72/ml5-spfx-extension

ml5 (friendly machine learning for the web) SharePoint Framework (SPFx) extension

azfarmo/Logistic-Regression-made-from-Scratch

FabioSmuu/artificial.js

This is an ongoing project intended to make it easier to use neural network creation, genetic algorithms, and other data science and machine learning skills.

jElhamm/Activation-Functions

"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "

pradeepdev-1995/Gradient-descent

Gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. To find a local minimum of a function using gradient descent, we take steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point. But if we instead take steps proportional to the positive of the gradient, we approach a local maximum of that function; the procedure is then known as gradient ascent.

stdlib-js/math-base-special-expit

Standard logistic function.

stdlib-js/math-base-special-logit

Logit function.

stdlib-js/math-iter-special-expit

Create an iterator which evaluates the standard logistic function for each iterated value.

stdlib-js/math-iter-special-logit

Create an iterator which evaluates the logit function for each iterated value.

tayal-sarthak/SeizureSeeker

(Sarthak Tayal, Annette Dao, Nora Michniewicz, Breanna Carez) Seizure Seeker is a browser-based tool that has trained data from EEG datasets to process EEG recordings to identify areas of seizure events/elevated neural activity. With one-second windows, it establishes a quiet baseline to detect seizure events above YOUR/an auto chosen threshold.

tech-espm/pic-plantrecogniser

Implementation of an ANN for recognisement of the Iris plant-family

amwata/gs-dynasty

e-commerce platform integrated with google appscript

Anas-github-acc/SigmoidNN

a neural network create to study the deep learning

BalajiN743/-Logistic-regression-bank-data-

HebaFahmy99/Logistic-Regression

Implementing a logistic regression program to predict whether a patient has heart disease or not based on some features.

JesusGMR96/SystemVerilog-Neural-Networks

SystemVerilog implementations of fundamental neural network structures, designed for synthesis on FPGAs.

mkgeiger/neural-network

Lightweight neural network library written in ANSI-C supporting prediction and backpropagation for Convolutional- and Fully Connected neural networks

mmaric27/BasicDNN

Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.

SameetAsadullah/clinical-risk-prediction

End-to-end binary classification pipeline for clinical risk prediction using PyTorch. Includes preprocessing, imbalanced data handling with SMOTE, optimizer benchmarking (SGD vs Adam), and performance visualization (AUC-ROC, Confusion Matrix). Designed to align with healthcare AI applications and model evaluation best practices.

shawntsai0312/NTUEE_ICDESIGN_23FALL_HW4

NTUEE IC Design 23Fall HW4

skosachiov/perceptron-with-sigmoid

This is a compact working example of a perceptron with sigmoid function in python.

TrentBrunson/Neural_Networks

TensorFlow 2.2, Keras, Deep Learning

zjykzj/RethinkingPAR

Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting