Randomized and quasi-randomized neural networks.

About | Back

nnetsauce is a tool for Statistical/Machine learning, in which pattern recognition is achieved by combining layers of randomized and quasi-randomized neural networks. These building blocks layers constitute the basis of many custom models, including models with deeper learning architectures; for regression, classification, and multivariate time series forecasting.

Information on package installation, use, documentation and source code (for contributing to its development) can be found through the following links:

- Read package/API documentation

- Contribute to package development/Read the source code

- See nnetsauce in action

Any question related to nnetsauce? Contact me.

Documentation | Back

If you want to install nnetsauce or read its documentation, readthedocs is the place.

Contributing/Source code | Back

If you want to contribute to nnetsauce's development or read its source code, package's source is available on GitHub

See nnetsauce in action | Back

If you want to see how nnetsauce works on many examples, and be informed about its recent developments, you can read these blog posts, and/or subscribe to this specific nnetsauce RSS feed.

Let's Talk ! | Back

Want to talk about nnetsauce? Email me at:

thierry DOT moudiki AT pm DOT me