Although 3-dimensional arrays are not the most common object used among the R projects, which are dominated by data.frame-like objects. However, when we’re starting to work with deep learning, (e.g. using {keras}), we can run into such objects m...

Although 3-dimensional arrays are not the most common object used among the R projects, which are dominated by data.frame-like objects. However, when we’re starting to work with deep learning, (e.g. using {keras}), we can run into such objects m...

Conditional RNN is one of the possible solutions if we’d like to make use of static features in time series forecasting. For example, we want to build a model, which can handle multiple time series with many different characteristics. It can be a mode...

In the previous year, I published a post, which as I hoped, was the first tutorial of the series describing how to effectively use PyTorch in Time Series Forecasting. Recently, a new exciting R package was submitted on CRAN. This great news was offici...

Remake About two weeks ago, I published on my blog a comparision between two possible implementation of double-dispatch: S4-based and vctrs-based. It turned out, that in my trials vctrs performed better. However, two days later I’ve got a message fr...

path.chain package provides an intuitive and easy-to-use system of nested objects, which represents different levels of some directory’s structure in the file system. It allows us to Look at the path.chain Sometimes one picture can say more, than a ...