diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index b65dcedbd8a10..2b3e83d64ab21 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -107,14 +107,9 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.resolution PR02" \
         -i "pandas.Timestamp.tzinfo GL08" \
         -i "pandas.Timestamp.year GL08" \
-        -i "pandas.api.types.is_dict_like PR07,SA01" \
-        -i "pandas.api.types.is_file_like PR07,SA01" \
         -i "pandas.api.types.is_float PR01,SA01" \
-        -i "pandas.api.types.is_hashable PR01,RT03,SA01" \
         -i "pandas.api.types.is_integer PR01,SA01" \
         -i "pandas.api.types.is_iterator PR07,SA01" \
-        -i "pandas.api.types.is_named_tuple PR07,SA01" \
-        -i "pandas.api.types.is_re PR07,SA01" \
         -i "pandas.api.types.is_re_compilable PR07,SA01" \
         -i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
         -i "pandas.arrays.ArrowExtensionArray PR07,SA01" \
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index f042911b53d2b..6adb34ff0f777 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -113,13 +113,24 @@ def is_file_like(obj: object) -> bool:
 
     Parameters
     ----------
-    obj : The object to check
+    obj : object
+        The object to check for file-like properties.
+        This can be any Python object, and the function will
+        check if it has attributes typically associated with
+        file-like objects (e.g., `read`, `write`, `__iter__`).
 
     Returns
     -------
     bool
         Whether `obj` has file-like properties.
 
+    See Also
+    --------
+    api.types.is_dict_like : Check if the object is dict-like.
+    api.types.is_hashable : Return True if hash(obj) will succeed, False otherwise.
+    api.types.is_named_tuple : Check if the object is a named tuple.
+    api.types.is_iterator : Check if the object is an iterator.
+
     Examples
     --------
     >>> import io
@@ -142,13 +153,24 @@ def is_re(obj: object) -> TypeGuard[Pattern]:
 
     Parameters
     ----------
-    obj : The object to check
+    obj : object
+        The object to check for being a regex pattern. Typically,
+        this would be an object that you expect to be a compiled
+        pattern from the `re` module.
 
     Returns
     -------
     bool
         Whether `obj` is a regex pattern.
 
+    See Also
+    --------
+    api.types.is_float : Return True if given object is float.
+    api.types.is_iterator : Check if the object is an iterator.
+    api.types.is_integer : Return True if given object is integer.
+    api.types.is_re_compilable : Check if the object can be compiled
+                                into a regex pattern instance.
+
     Examples
     --------
     >>> from pandas.api.types import is_re
@@ -275,13 +297,22 @@ def is_dict_like(obj: object) -> bool:
 
     Parameters
     ----------
-    obj : The object to check
+    obj : object
+        The object to check. This can be any Python object,
+        and the function will determine whether it
+        behaves like a dictionary.
 
     Returns
     -------
     bool
         Whether `obj` has dict-like properties.
 
+    See Also
+    --------
+    api.types.is_list_like : Check if the object is list-like.
+    api.types.is_file_like : Check if the object is a file-like.
+    api.types.is_named_tuple : Check if the object is a named tuple.
+
     Examples
     --------
     >>> from pandas.api.types import is_dict_like
@@ -308,13 +339,22 @@ def is_named_tuple(obj: object) -> bool:
 
     Parameters
     ----------
-    obj : The object to check
+    obj : object
+        The object that will be checked to determine
+        whether it is a named tuple.
 
     Returns
     -------
     bool
         Whether `obj` is a named tuple.
 
+    See Also
+    --------
+    api.types.is_dict_like: Check if the object is dict-like.
+    api.types.is_hashable: Return True if hash(obj)
+                                  will succeed, False otherwise.
+    api.types.is_categorical_dtype : Check if the dtype is categorical.
+
     Examples
     --------
     >>> from collections import namedtuple
@@ -340,9 +380,24 @@ def is_hashable(obj: object) -> TypeGuard[Hashable]:
     Distinguish between these and other types by trying the call to hash() and
     seeing if they raise TypeError.
 
+    Parameters
+    ----------
+    obj : object
+        The object to check for hashability. Any Python object can be passed here.
+
     Returns
     -------
     bool
+        True if object can be hashed (i.e., does not raise TypeError when
+        passed to hash()), and False otherwise (e.g., if object is mutable
+        like a list or dictionary).
+
+    See Also
+    --------
+    api.types.is_float : Return True if given object is float.
+    api.types.is_iterator : Check if the object is an iterator.
+    api.types.is_list_like : Check if the object is list-like.
+    api.types.is_dict_like : Check if the object is dict-like.
 
     Examples
     --------