Recurrent Neural Network refers to a specific architecture of an artificial neural network that work well for arbitrary sequence datasets of big data. Such a Recurrent Neural Network (RNN) consists of cyclic connections that...
Long Short Term Memory (LSTM) represents a specific architecture of a recurrent neural network (RNN) that works well with big data. It is perfectly suited to model temporal sequences and long-range dependencies thus outperforming...
Long Short Term Memory Tutorial offers a collection of rated resources and pieces of information about using this innovative deep learning technique in order to work with big data. The Long Short Term Memory...
Tensor Machine Learning refers to a concept of using a multi-dimensional array when learning from big data in a specific way. More general information about a tensor can be found in our article What...
What is a Tensor is an often asked question whereby a short answer often used is that it is a multi-dimensional array used in big data analysis often today. In particular with deep learning...
AlexNet is considered as a standard architecture for a Convolutional Neural Network that is able to learn from big data. It is a relatively large CNN model with five convolution layers and three fully...
Neural network learning is a well defined process but involved a wide variety of hyper-parameters in order to correctly learn from big data. More general information about the architectures and types of an artificial...
A deep learning tutorial is a great source in order to understand how to use this new machine learning paradigm with big data. There are a wide variety of tutorials available that all have...
Generalization in Machine Learning is a very important element when using machine learning algorithms with big data. For example the key goal of a machine learning classification algorithm is to create a learning model...
SVM train stands for a process in machine learning that creates a Support Vector Machine (SVM) model by learning from big data. There are several ways how such a model can be trained and...
