CIFAR 10 image dataset
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Updated
Nov 20, 2024 - Python
CIFAR 10 image dataset
Deep Learning
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.
Compare vanishing gradient problem case by case.
Simple multi layer perceptron application using feed forward back propagation algorithm
"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "
A classical XOR neural network using pytorch
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.
Neural Network from scratch without any machine learning libraries
Standard logistic function.
Logit function.
Implementing a logistic regression program to predict whether a patient has heart disease or not based on some features.
Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting
A implementation of a Neural Network in vanilla python that trains on the MNIST handwritten digit classifiction problem.
Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.
This is a compact working example of a perceptron with sigmoid function in python.
We introduce two novel hybrid activation functions: S3 (Sigmoid-Softsign) and its improved version S4 (Smoothed S3)
Introductory level artificial neural network
A simple PyTorch-based neural network that classifies student exam outcomes (Pass/Fail) using study hours and previous exam scores. Implements dataset splitting (train/val/test), mini-batch training, and evaluation with configurable hyperparameters.
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