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* ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== ))) |
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-* ((( ==== **[[Intermediate >>||anchor = "HIntermediate-1"]]** ==== ))) |
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=== **Beginner** === |
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=== [[Creating a simple cell optimisation>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb||rel=" noopener noreferrer" target="_blank"]] === |
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**Level**: beginner(%%) **Type**: interactive tutorial |
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This notebook will explain how to optimise a model using the covariance matrix adaptation (CMA) optimisation strategy. BluePyOpt includes two flavors of CMA: a single objective one and a hybrid single/multi objective one. |
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-=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] === |
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-**Level**: beginner(%%) **Type**: interactive tutorial |
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-This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt. |
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-=== **Intermediate** === |
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-=== [[Creating an optimisation with meta parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/metaparameters/metaparameters.ipynb||rel=" noopener noreferrer" target="_blank"]] === |
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-**Level**: intermediate(%%) **Type**: interactive tutorial |
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-This notebook will explain how to set up an optimisation that uses metaparameters (parameters that control other parameters) |
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