fixed doc following code review.

doc/library/sparse/index.txt

@@ -149,7 +149,7 @@ List of Implemented Operations
       The grad implemented is regular.
 
 - Transpose
-    - :func:`Transpose <theano.sparse.basic.transpose>`.
+    - :func:`transpose <theano.sparse.basic.transpose>`.
       The grad implemented is regular.
 
 - Basic Arithmetic

doc/library/typed_list.txt

@@ -8,7 +8,7 @@
 
     This is not in the released version 0.6.0, but will be in the next release (0.7 or 0.6.1).
 
-This is a type that represent a list in Theano. All element must have
+This is a type that represents a list in Theano. All elements must have
 the same Theano type. Here is an example::
 
     import theano.typed_list
@@ -20,8 +20,8 @@ the same Theano type. Here is an example::
     print f([[1, 2, 3], [4, 5]], [2])
     #[array([ 1.,  2.,  3.], dtype=float32), array([ 4.,  5.], dtype=float32), array([ 2.], dtype=float32)]
 
-A second example with Scan. Scan don't have yet direct support of
-TypedList, so you can only use it as non_sequences(not in sequences or
+A second example with Scan. Scan doesn't yet have direct support of
+TypedList, so you can only use it as non_sequences (not in sequences or
 as outputs).::
 
     import theano.typed_list

theano/sparse/basic.py

@@ -1112,8 +1112,8 @@ If you want to take only one element of a sparse matrix see
 The above indexing methods are not supported because the return value
 would be a sparse matrix rather than a sparse vector, which is a
 deviation from numpy indexing rule.  This decision is made largely
-for keeping the consistency between numpy and theano. Subjected
-to modification when sparse vector is supported.
+to preserve consistency between numpy and theano. This may be revised
+when sparse vectors are supported.
 
 :param x: Sparse matrix.
 :param index: Tuple of slice object.
@@ -1169,13 +1169,13 @@ class GetItemScalar(gof.op.Op):
 
 get_item_scalar = GetItemScalar()
 """Implement a subtensor of a sparse variable that take
-two scalar as index and return a scalar.
+two scalars as index and return a scalar.
 
 If you want to take a slice of a sparse matrix see
-`GetItem2d` that return a sparse matrix.
+`GetItem2d` that returns a sparse matrix.
 
 :param x: Sparse matrix.
-:param index: Tuple of scalar..
+:param index: Tuple of scalars.
 
 :return: The item corresponding in `x`.
 
@@ -1502,18 +1502,18 @@ def sp_sum(x, axis=None, sparse_grad=False):
     axis.
 
     It operates a reduction along the axis specified. When
-    `axis` is `None`, it is apply along all axis.
+    `axis` is `None`, it is apply along all axes.
 
     :param x: Sparse matrix.
-    :param axis: Axis along the sum is apply. Integers or `None`.
+    :param axis: Axis along which the sum is applied. Integers or `None`.
     :param sparse_grad: `True` to have a structured grad. Boolean.
 
     :return: The sum of `x` in a dense format.
 
     :note: The grad implementation is controlled with the `sparse_grad`
            parameter. `True` will provide a structured grad and `False`
-           will provide a regular grad. For both choice, the grad
-           return a sparse matrix having the same format as `x`.
+           will provide a regular grad. For both choices, the grad
+           returns a sparse matrix having the same format as `x`.
     :note: This op does not return a sparse matrix, but a dense tensor
            matrix.
     """