We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
1 parent 80bfec7 commit 8c84ad1Copy full SHA for 8c84ad1
docs/templates/scikit-learn-api.md
@@ -1,4 +1,4 @@
1
-# Wrappers for the Sciki-Learn API
+# Wrappers for the Scikit-Learn API
2
3
You can use `Sequential` Keras models (single-input only) as part of your Scikit-Learn workflow via the wrappers found at `keras.wrappers.sklearn.py`.
4
@@ -42,4 +42,4 @@ fitting (predicting) parameters are selected in the following order:
42
When using scikit-learn's `grid_search` API, legal tunable parameters are
43
those you could pass to `sk_params`, including fitting parameters.
44
In other words, you could use `grid_search` to search for the best
45
-`batch_size` or `nb_epoch` as well as the model parameters.
+`batch_size` or `nb_epoch` as well as the model parameters.
0 commit comments