=============== Getting Started =============== Halerium can be either used online on the Halerium platform or locally as a pure Python package. To get your test account for the Halerium platform visit https://erium.de/ For local usage follow the installation instructions: .. toctree:: :maxdepth: 1 installation High level usage ================ For the most common applications Halerium offers the convenient ``CausalStructure`` class at the package level. With this class you can easily create, train and evaluate Bayesian models with just a couple of lines. :: from halerium import CausalStructure causal_structure = CausalStructure([input_columns, output_columns]) causal_structure.train(training_data_frame) causal_structure.predict(test_data_frame) To learn more about the usage of the high-level package check out .. toctree:: :maxdepth: 1 examples_high code_high Low level usage =============== With the halerium.core package you can build custom tailored Halerium graphs, with which you can model arbitrarily complex processes. You choose how much knowledge is hard-coded into your graph and how much is to be learned from data. Build deep hierarchical graphs with Variables of arbitrary dimensions and complex tensor operations. Combine a graph with incomplete data and let halerium solve your model for you. Utilize the powerful combination of Bayesian inference and machine learning without caring about the statistical details! :: import halerium.core as hal with hal.Graph("g") as g: hal.Variable("x", shape=(3, 5), mean=0., variance=1.) hal.Variable("y", shape=(3,)) y.mean = hal.sigmoid(hal.sum(x, axis=1)) y.variance = hal.tensordot(x, x, axes=2) model = hal.get_posterior_model(g, data={g.y: [1, 2, 3]}) model.get_means(g.x) >>> array([[[0.14381036, 0.14378252, 0.14378723, 0.14380088, 0.14379767], [0.32230996, 0.32230319, 0.3222988 , 0.3222934 , 0.32231929], [0.41568274, 0.41570946, 0.41568607, 0.41570675, 0.41571199]]]) Check out the in-a-nutshell introduction in .. toctree:: :maxdepth: 1 examples/01_introduction/01_building_blocks Find more examples and the code overview in .. toctree:: :maxdepth: 1 examples_core code_core The advantages of halerium.core compared to conventional machine learning are illustrated in the :ref:`advantages` section.