MLP-Numpy - A simple modular implementation of Multi Layer Perceptron in pure Numpy.

Last update: Jan 01, 2022

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Overview

MLP-Numpy

A simple modular implementation of Multi Layer Perceptron in pure Numpy. I used the Iris dataset from scikit-learn library for the experiments.

Features

Fully modular and configurable
Different learning rates can be used for different layers and iterations. (Dynamic learning rate)
Pure numpy with no additional dependecies
Supports Linear, Softmax, Sigmoid, TanH, and ReLU activations

Owner

Soroush Omranpour

Musician, Deep learning Engineer.

GitHub Repository

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MLP-Numpy - A simple modular implementation of Multi Layer Perceptron in pure Numpy.

Related tags

Overview

MLP-Numpy

Features

Owner

Soroush Omranpour

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