Running Deeper C++/C/Java

Today, I tried writing a Generative Adversarial Network. Using the MNIST Data set, I will be writing a GAN that will create images of numbers as close to the dataset as possible. Currently, I have been getting stuck, the generator doesn't generate proper images. GAN works with two neural nets, one was a generator, the other being a discriminant. The generator creates images from random noise, th..

A convolution is a k*k grid of an image, that the CNN can read and analyze. Unlike a normal neural network, a convolutional neural network can incorporate the 2D style of the original image, resulting in a much higher accuracy than a normal neural network. Below is a nice explanation from Medium.org. Convolution 2. Convolving an image with a filter We take the 5*5*3 filter and slide it over the ..

Neural Networks consist of many nodes, edges, and algorithms. Nodes: Input layer, Hidden Layers, Output Layer Input Layer: Nodes with input values, each dataset consists of many different input layers. Hidden Layers: Consist of Values + Algorithm, Algorithm: activation functions that change values. Edges consist of weights, more layers mean higher power function capability Each edge is a linear ..