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This project implements a Perceptron, which is a fundamental algorithm used in machine learning for binary classification tasks. The Perceptron learns from a set of training data and adjusts its weights to classify new data points.
Implementation of perceptron algorithm for both classification and regression tasks. Trained a CNN model on the MNIST dataset and also implemented the autoencoder to denoise the noisy MNIST dataset.
projeto de Machine Learning com modelos lineares: Perceptron Algorithm Learning, Regressão linear e Regressão logística para classificação em uma adaptação do MNIST Dataset
The perceptron algorithm is the basic algorithm for classification, which serves as the backbone of the Neural Networks and SVM linear classification. This code will provide a deep understanding of the algorithm by taking you through it from scratch.
This is the repository for the EDAF70 - Tillämpad artificiell intelligens (Applied Artificial Intelligence) course given at Lunds Tekniska Högskola (LTH) during the Spring 2019 term.