The causal Data Science tools
Bayesian Networks & Biochemical Intelligence for Healthcare
Tzager is the first Bayesian Inference Python library, that can be used in real market projects in Healthcare. Take advantage of Tzager’s already existing vast Healthcare Bayesian Network to infer probabilities and connect causalities by simply using Tzager’s functions in your projects.
We created the closest to an A.I. Bayesian Brain with human-like logic in HealthcareLearn more
Introducing Tzager’s Bayesian Inference library in PythonLearn more
How Tzager works?
Use Cases of the Python library
In this example we showcase the standard bayesian function of the tzager library, which allows researchers to create their own Bayesian inference algorithms by using their own bayesian networks. We assume a typical Bayesian network with given variables, a designed topology and Conditional Probability Tables. (see documentation).
Pip install tzager and have immediate access to the free version of the library.
Create your own Bayesian Networks.
For the first time you will have the opportunity to create your own Bayesian Networks from your samples or data in a couple of steps. If you are working on Healthcare, you should probably consider the premium option.
Request for free demo access to test the powerful Bayesian Networks and Causal Mechanisms in your projects. Get access in the tzager.com platform and use powerful visualisations, while using the Tzager Workflow tools.
Get your Licence and accelerate your healthcare research. Contact us at email@example.com or complete the request demo form.
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