mustafa-pnevma-galinis Goto Github PK

neural-nets

Programming Assignments and Lectures for Geoffrey Hinton's "Neural Networks for Machine Learning" Coursera course

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

object-cloning

objectcrosspass

Providing an object to a method and use it in the inner method implementation

pillow

The friendly PIL fork (Python Imaging Library)

py

Repository to store sample python programs for python learning

python_shapes

resnet

Implementing ResNet from scratch in Keras

space-nexus

This Application is dedicated to deal with scientific theories with a religious prespective and try to illustrate most important points in it.

statistical-analysis-python-tutorial

Statistical Data Analysis in Python

training-a-neural-network-with-backpropagation-mathematics

Backpropagation is a widely used algorithm in training feedforward neural networks for supervised learning. It computes the gradient of the loss function with respect to the different weights and bias by using the chain rule of differential calculus. These gradients are used to update the weights and bias. Since these gradients are learned in the backward direction, starting from the output node, this learning process is referred to as the backward propagation. This work attempts to explain how backpropagation works with the help of a concrete example.

using-hashmap-through-asynctask

That regarding using hashmap to retrieve data from an API, rather than using (String[])