... |
... |
@@ -14,9 +14,4 @@ |
14 |
14 |
**Level**: beginner(%%) **Type**: interactive tutorial |
15 |
15 |
|
16 |
16 |
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. |
17 |
|
-=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] === |
18 |
18 |
|
19 |
|
-**Level**: beginner(%%) **Type**: interactive tutorial |
20 |
|
- |
21 |
|
-This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt. |
22 |
|
- |