A collection of machine learning projects, including Face Recognition using KNN and various algorithms and techniques. This repo offers practical implementations and resources for exploring machine learning.

Artificial Intelligence, Deep Learning: training an artificial neural network using backpropagation with gradient descent .

I create this project for learning about neural network

A speculative mechanism to accelerate long-latency off-chip load requests by removing on-chip cache access latency from their critical path, as described by MICRO 2022 paper by Bera et al. (https://arxiv.org/pdf/2209.00188.pdf)

In this repo I have added Perceptron training rule is a topic of machine learning in which we use our activation function and neural network and update our weights if there is an error in actual output or output that we had to matched.

spam email detection using perceptron learning algorithm

Building an agent-based trip-generation and assignment model with primitive knowledge agent initialisation using a genetic algorithm

A collection of various applied Machine Learning and Artificial Intelligence projects I have done.

This repository features a collection of classical and modern pattern recognition techniques, from PCA and LDA to Perceptron and CNNs

Implementing 2 basic classification algorithms: K-Nearest Neighbor (KNN) and Perceptron Learning Algorithm (PLA) to predict the likelihood of customers subscribing to term deposits. The implementation process from manual calculation based on mathematical formulas to utilizing libraries.

This is a JavaScript program that simulates an AI agent going to the store, buying items, and heading home. Perceptrons are used to help the agent make decisions in the program.

Training single-layer perceptrons to get the outputs of OR and AND logic gates.

A RNA (Rede Neural Artificial) Perceptron é um dos modelos mais simples de rede neural, sendo a base para redes neurais mais complexas. É um classificador linear usado principalmente para problemas de classificação binária. A seguir, descrevemos o funcionamento básico do Perceptron.

This repository contains fun coding!

M.Sc Data Science Related Works

A prova de convergência do procedimento de aprendizado proposto por Rosenblatt é conhecida como teorema de convergência do perceptron. O perceptron construído em torno de um único neurônio é limitado a realizar classificação de padrões com apenas duas classes (hipóteses).

A Multilayer Perceptron Neural Network implementation written in ANSI-C.

perceptron implementation in rust

Implementing perceptron alogorithm in python using Numpy and Pandas