一文彻底搞懂BP算法:原理推导+数据演示+项目实战
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Updated
Jul 2, 2019 - Python
一文彻底搞懂BP算法:原理推导+数据演示+项目实战
Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation
Back Propagation, Python
Minimalist deep learning library with first and second-order optimization algorithms made for educational purpose
Neural network/Back Propagation implemented from scratch for MNIST.从零开始实现神经网络和反向传播算法,识别MNIST
Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks
MNIST Classification using Neural Network and Back Propagation. Written in Python and depends only on Numpy
Implementation of the back-propagation algorithm using only the linear algebra and other mathematics tool available in numpy and scipy.
Multivariate Regression and Classification Using a Feed-Forward Neural Network and Gradient Descent Optimization.
[RU] Обучение многослойного перцептрона с одним скрытым слоем методом обратного распространения ошибки. [EN] Training of a multilayer perceptron with one hidden layer by the back-propagating errors method.
Using only numpy in Python, a neural network with a forward and backward method is used to classify given points (x1, x2) to a color of red or blue.
Demonstration of the mini-lab (practical) component activities conducted for the course of Neural Networks and Deep Learning (19CSE456).
Implementing the backpropagation algorithm for Neural Networks
A mini-Library consisting of the implementation of classes/functions useful for Machine Learning Applications.
Neural Network implementation with Numpy
Automatic backpropagation implemented in numpy,
Auto Propagation System for Complex Neural Networks of Luma Python library
Simple Multi-Layer Perceptron(MLP) with forward and backward propagation
Multi-Layer Perceptron Implementation
A Numpy based implementation to understand the backpropagation algorithm using the XOR Problem.
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