Archive | Deep Learning

A Demonstration of Memory in a Long Short-Term Memory Network

Demonstration of Memory with a Long Short-Term Memory Network in Python

Long Short-Term Memory (LSTM) networks are a type of recurrent neural network capable of learning over long sequences. This differentiates them from regular multilayer neural networks that do not have memory and can only learn a mapping between input and output patterns. It is important to understand the capabilities of complex neural networks like LSTMs […]

Continue Reading 2
How to Use Weight Regularization with LSTM Networks for Time Series Forecasting

How to Use Weight Regularization with LSTM Networks for Time Series Forecasting

Long Short-Term Memory (LSTM) models are a recurrent neural network capable of learning sequences of observations. This may make them a network well suited to time series forecasting. An issue with LSTMs is that they can easily overfit training data, reducing their predictive skill. Weight regularization is a technique for imposing constraints (such as L1 […]

Continue Reading 15