Bonsai.ML.HiddenMarkovModels.Design 0.0.1002

Bonsai - Machine Learning

The Bonsai.ML project is a collection of packages designed to integrate machine learning algorithms with Bonsai. This document provides an overview of the available packages and their functionalities.

Core Packages

• Bonsai.ML Provides common tools and functionality.

• Bonsai.ML.Design Provides common tools and functionality for visualizers and editor features.

• Bonsai.ML.Data Provides common tools and functionality for working with data.

• Bonsai.ML.Python Provides common tools and functionality for C# packages to interface with Python.

Available Packages

Bonsai.ML.LinearDynamicalSystems

Facilitates inference using linear dynamical systems (LDS). It interfaces with the lds_python package using the Bonsai - Python Scripting library.

• Bonsai.ML.LinearDynamicalSystems.Kinematics Supports the use of the Kalman Filter for inferring kinematic data.

• Bonsai.ML.LinearDynamicalSystems.LinearRegression Utilizes the Kalman Filter to perform online Bayesian linear regression.

Bonsai.ML.LinearDynamicalSystems.Design

Visualizers and editor features for the LinearDynamicalSystems package.

Bonsai.ML.HiddenMarkovModels

Facilitates inference using Hidden Markov Models (HMMs). It interfaces with the ssm package using the Bonsai - Python Scripting library.

• Bonsai.ML.HiddenMarkovModels.Observations Provides functionality for specifying different types of observations.

• Bonsai.ML.HiddenMarkovModels.Transitions Provides functionality for specifying different types of transition models.

Bonsai.ML.HiddenMarkovModels.Design

Visualizers and editor features for the HiddenMarkovModels package.

Bonsai.ML.Torch

Interfaces with the TorchSharp package, a C# wrapper around the torch library. Provides tooling for manipulating tensors, performing linear algebra, training and inference with deep neural networks, and more.

[!NOTE] Bonsai.ML packages can be installed through Bonsai's integrated package manager and are generally ready for immediate use. However, some packages may require additional installation steps. Refer to the specific package section for detailed installation guides and documentation.

Development Roadmap

The ultimate goal of the Bonsai.ML project is to bring powerful machine learning tools into Bonsai to enable intelligent experimental control. To achieve this, our plan is to incorporate several different packages, models, frameworks, and language integrations. You can follow our progress by going to the Bonsai ML development roadmap.

Feedback and Contributions

Bonsai.ML is an open-source project and we welcome contributions and feedback from the community. If you have any comments or questions, or require assistance, please feel free to open an issue on the GitHub repo. If you would like to contribute to the project, please see our Contributor Guide. By contributing to our project, we also expect you to uphold our community Code of Conduct.

Acknowledgments

Development of the Bonsai.ML package is supported by the Biotechnology and Biological Sciences Research Council [grant number BB/W019132/1].