Implement Back Propagation in deep neural network (DNN).

This is a repository for Multi-Layer Perceptron and Logistic Regression. There is a code (function) for Logistic Regression. SOme analysis is performed on the function. This is compared with the sklearn Logistic Regression function. Then, the decision boundary has also been plotted for the classification. The next part is the basic neural networ…

Implementing an Image classification neural network to classify Street House View Numbers

Understanding DNN

A feedforward multilayer perceptron with gradient descent & backpropagation written from scratch in Java

step by step tutorial for ANN

Javascript implementation of some activation functions.

Design of a CNN (Convolutional Neural Networks) to classify CIFAR-10 images

A small walk-through to show why ReLU is non linear!

m-arcsinh: A Reliable and Efficient Function for Supervised Machine Learning (scikit-learn, TensorFlow, and Keras) and Feature Extraction (scikit-learn)

Source for the paper "Universal Activation Function for machine learning"

Deep Learning concepts practice using Cifar-10 dataset

📦 Non-official SPOCU activation function implementation for Pytorch and Tensorflow.

Hyper-Flexible Convolutional Neural Networks Based on Generalized Lehmer and Power Means

Neural_Networks_From_Scratch

PyTorch implementation of the Leaky Hardtanh activation function

Logit-space logical activation functions for pytorch

✅ Optimized Swish activation function, for neural networks

Artificial Intelligence Learning Notes.

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.