Comparison of a very simple regression in tensorflow and keras

In this short post we perform a comparative  analysis of a very simple regression problem in tensorflow and keras. We start off with an eye-catching plot, representing the functioning of an optimizer using the stochastic gradient method. The plot is explained in more detail further below.  A 3 rotatable …

Knime – Multivariate time series

Intro: Knime is a  very powerful machine learning tool, particularly suitable for the management of complicated workflows as well as rapid prototyping. It has recently become yet more useful with the arrival of easy-to-use Python nodes. This is true because sometimes the set of nodes – which is large – …

Multivariate Time Series Forecasting with Neural Networks (3) – multivariate signal noise mixtures

In this follow up post we apply the same methods we developed previously to a different dataset. In this third post we mix the previous two datasets. So, on the one hand, we have noise signals, on the other hand we have innovators and followers.

Multivariate Time Series Forecasting with Neural Networks (1)

In this post we present the results of a competition between various forecasting techniques applied to multivariate time series. The forecasting techniques we use are some neural networks, and also – as a benchmark – arima. In particular the neural networks we considered are long short term memory (lstm) networks, and dense …