diff --git a/doc/datasets/index.rst b/doc/datasets/index.rst
index 77ecc05c710..76561e7990a 100644
--- a/doc/datasets/index.rst
+++ b/doc/datasets/index.rst
@@ -50,7 +50,7 @@ These functions return a tuple ``(X, y)`` consisting of a ``n_samples`` *
 ``n_features`` numpy array ``X`` and an array of length ``n_samples``
 containing the targets ``y``.
 
-In addition, there are also miscellanous tools to load datasets of other 
+In addition, there are also miscellaneous tools to load datasets of other 
 formats or from other locations, described in the :ref:`loading_other_datasets`
 section. 
 
@@ -171,8 +171,9 @@ near-equal-size classes separated by concentric hyperspheres.
 :func:`make_circles` and :func:`make_moons` generate 2d binary classification
 datasets that are challenging to certain algorithms (e.g. centroid-based
 clustering or linear classification), including optional Gaussian noise.
-They are useful for visualisation. produces Gaussian
-data with a spherical decision boundary for binary classification.
+They are useful for visualisation. :func:`make_circles` produces Gaussian data
+with a spherical decision boundary for binary classification, while
+:func:`make_moons` produces two interleaving half circles.
 
 Multilabel
 ~~~~~~~~~~
@@ -261,7 +262,7 @@ Sample images
 -------------
 
 Scikit-learn also embed a couple of sample JPEG images published under Creative
-Commons license by their authors. Those image can be useful to test algorithms
+Commons license by their authors. Those images can be useful to test algorithms
 and pipeline on 2D data.
 
 .. autosummary::