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README.md

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@@ -16,6 +16,9 @@ The required modules can then be installed with
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```bash
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pip install -r requirements.txt
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```
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or
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`pip install .`
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which will install the entire package via pip
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# Running
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Running the package is also simple. Simply do
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Here FitterKwargs is now split into sub-settings with `BuildSettings` being passed to the model `compile` method, `FitSettings` setting up training information, and `Layers` defining the types + kwargs of each layer in the model. New layers can be implemented in the `__TF_LAYER_IMPLEMENTATIONS` object which lives in `machine_learning/tf_interface`
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# Executables
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Simply run `python MachineLearningMCMC -c /path/to/toml/config` and it'll automatically run the chain.
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# Implementing a New Fitter
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Implementing a new fitter is relatively simple. Most implementing is done in `machine_learining/ml_factory/MLFactory`. For Scikit-Learn based models, the new method just needs to imported and added to the `scikit` entry in `__IMPLEMENTED_ALGORITHMS`.
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