We designed, implemented and compared various regression and classification models on Diabetics patient data.
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Updated
May 5, 2020
We designed, implemented and compared various regression and classification models on Diabetics patient data.
Implementation of a perceptron class. There are no restrictions on the number of layers. It is possible to select the activation function (only 3 so far) for each layer and adjust the training parameters of the perceptron. Presence of examples = True
Neural networks from scratch. No TensorFlow, just NumPy.
Predicting on Breast Cancer data using Neural Networks in PyTorch.
Learning how artificial neural networks work through a multi layer perceptron using error back propagation.
Clasificador de patrones matriciales de letras usando redes neuronales y perceptrón multicapa (MLP). TPI del año 2022 para la asignatura Inteligencia Artificial de la UTN FRRe
Simulate synaptic caching with a multilayer perceptron
USP - ACH2016 - Inteligência Artificial - Implementação de um Multilayer Perceptron
Deepfakes detection by machine learning and deep learning
Machine Learning - 2019 project @ Unisi, Italy
Basic neural networks implemented by plain numpy
Emoji and MNIST digit Classfication
Coursework for CS5173 - Deep Learning. Dual level (Graduate/Undergraduate) course introducing deep learning theory and practice.
A Deep Learning Tensorflow Model which uses Sonar Dataset for identifying rock or mine from its reflecting frequency, using Gradient Descent Optimizer
📚 A basic C# MLP/ANN library
Custom multilayer perceptron (MLP)
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