So what exactly is Keras? Let's put it this way, it makes programming machine learning algorithms much much easier. It simply runs atop Tensorflow/Theano, cutting down on the coding and increasing ...

Most neural network libraries, including PyTorch, scikit and Keras, have built-in MNIST datasets. However, working with pre-built MNIST datasets has two big problems. First, a pre-built dataset is a ...

Convolutional Neural Network from scratch Live Demo Objective of this work was to write the Convolutional Neural Network without using any Deep Learning Library to gain insights of what is actually ...

Artificial intelligence and more specifically, machine learning, with human augmentation requires a thorough strategy to achieve a breakthrough.

In this article, we will implement the multiclass image classification using the VGG-19 Deep Convolutional Network used as a Transfer Learning framework where the VGGNet comes pre-trained on the ...

Five ILSVRC-2010 test images in the first column. Remaining columns show the training images that produce feature vectors in the last hidden layer with the smallest Euclidean distance from the feature ...

In most discussions, deep learning means using deep neural networks. There are, however, a few algorithms that implement deep learning using other kinds of hidden layers besides neural networks.