fix accidental overwrite of README.rst of 2b37817

Author: basnijholt

README.rst

@@ -27,10 +27,6 @@ to see examples of how to use ``adaptive`` or visit the
 
 .. summary-end
 
-**WARNING: adaptive is still in a beta development stage**
-
-.. not-in-documentation-start
-
 Implemented algorithms
 ----------------------
 
@@ -46,6 +42,8 @@ but the details of the adaptive sampling are completely customizable.
 
 The following learners are implemented:
 
+.. not-in-documentation-start
+
 - ``Learner1D``, for 1D functions ``f: ℝ → ℝ^N``,
 - ``Learner2D``, for 2D functions ``f: ℝ^2 → ℝ^N``,
 - ``LearnerND``, for ND functions ``f: ℝ^N → ℝ^M``,
@@ -54,10 +52,16 @@ The following learners are implemented:
 - ``AverageLearner1D``, for stochastic 1D functions where you want to
   estimate the mean value of the function at each point,
 - ``IntegratorLearner``, for
-  when you want to intergrate a 1D function ``f: ℝ → ℝ``,
+  when you want to intergrate a 1D function ``f: ℝ → ℝ``.
 - ``BalancingLearner``, for when you want to run several learners at once,
   selecting the “best” one each time you get more points.
 
+Meta-learners (to be used with other learners):
+
+- ``BalancingLearner``, for when you want to run several learners at once,
+  selecting the “best” one each time you get more points,
+- ``DataSaver``, for when your function doesn't just return a scalar or a vector.
+
 In addition to the learners, ``adaptive`` also provides primitives for
 running the sampling across several cores and even several machines,
 with built-in support for
@@ -67,7 +71,6 @@ with built-in support for
 `ipyparallel <https://ipyparallel.readthedocs.io/en/latest/>`_ and
 `distributed <https://distributed.readthedocs.io/en/latest/>`_.
 
-
 Examples
 --------