This section hosts a variety of articles, tutorials and explanations of concepts and workflows that integrate with the FluCoMa tools and the wider gamut of machine learning and machine listening technologies.

A video tutorial guiding that teaches you how to build a two-dimensional corpus exploration patch in Max.

Batch processing corpora with the Fluid Corpus Manipulation toolkit.

Decompose an audio buffer into component parts using non-negative matrix factorisation.

This video tutorial guides you through building a flexible sound classifier.

Normalize, Standardize, & RobustScale

A quick overview of the decomposition tools in the FluCoMa toolkit.

Histograms, distribution functions, and the normal distribution

A resource for pedagogues wanting to teach FluCoMa

Commonly used spectral analysis method

Some suggestions for getting started exploring FluCoMa

A small overview for how median filters work.

A guide on using the parameters of and MLP.

An overview of how neural networks learn.

Some thinking about outliers and how to manage them.

Using statistics to refine the analysis of pitch content.

Video tutorial introducing the FluidMLPRegressor neural network.

Prevent outliers from negatively impacting BufStats' statistical summary.

Initialize non-negative matrix factorization with seeded elements.

Bundling time by smoothing windows of data.

Strategies for encoding and explaining time to a computer.

Determine if a neural network is overfit by reserving some testing data

Apply weights to BufStats

The affects of scaling on measures of similarity