Cilimkovic, M. (2015) Neural Networks and Back Propagation Algorithm. Institute of Technology Blanchardstown, 15, 3-7.

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners!

Learn some best practices and tips for coding backpropagation from scratch for neural networks. Understand the math, choose a framework, use vectorization, test, debug, and optimize your code.

ai deep-learning neural-network pytorch artificial-intelligence gradient-descent backpropagation backpropagation-algorithm adam-optimizer Updated on May 8, 2023 Python ...

A backpropagation algorithm is implemented in Python from scratch to perform a classification analysis.

A general backpropagation algorithm is proposed for feedforward neural network learning with time varying inputs. The Lyapunov function approach is used to rigo ...

This article proposes a sparsity-driven SNN learning algorithm, namely backpropagation with sparsity regularization (BPSR), aiming to achieve improved spiking and synaptic sparsity. Backpropagation ...

Once this model is pre-trained, we use energy-based decoding that relies on the backpropagation algorithm to use the output from a source language decoder as additional input to generate a sentence in ...