docs: page headers made consistent, ranked batch query page removed from index.rst (the page is not fully written yet)

Author: cosmic-cortex

docs/source/content/examples/Keras-integration.rst

@@ -1,5 +1,5 @@
-Bringing your Keras models to modAL workflows
-=============================================
+Keras models in modAL workflows
+===============================
 
 Thanks for the scikit-learn API of Keras, you can seamlessly integrate Keras models into your modAL workflow. In this tutorial, we shall quickly introduce how to use the scikit-learn API of Keras and we are going to see how to do active learning with it. More details on the Keras scikit-learn API `can be found here <https://keras.io/scikit-learn-api/>`__.
 

docs/source/content/examples/active_regression.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Active regression with Gaussian processes\n",
+    "# Active regression\n",
     "In this example, we are going to demonstrate how can the ActiveLearner be used for active regression using Gaussian processes. Since Gaussian processes provide a way to quantify uncertainty of the predictions as the covariance function of the process, they can be used in an active learning setting."
    ]
   },
@@ -229,7 +229,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.6.5"
   }
  },
  "nbformat": 4,

docs/source/content/examples/ensemble_regression.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Active regression with Committee\n",
+    "# Ensemble regression\n",
     "With an ensemble of regressors, the standard deviation of the predictions at a given point can be thought of as a measure of disagreement. This can be used for active regression. In the following example, we are going to see how can it be done using the CommitteeRegressor class.\n",
     "\n",
     "The executable script for this example can be [found here!](https://github.com/cosmic-cortex/modAL/blob/master/examples/ensemble_regression.py)\n",
@@ -234,7 +234,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.6.5"
   }
  },
  "nbformat": 4,

docs/source/content/examples/extending_modal.ipynb

@@ -99,7 +99,7 @@ strategy is as easy as the following.
     )
 
 For more details on how to implement your custom strategies, visit the
-page :ref:`Extending-modAL`!
+page `Extending modAL <content/overview/Extending-modAL.ipynb>`_!
 
 An example with active regression
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

docs/source/content/overview/Extending-modAL.ipynb

@@ -95,8 +95,7 @@ strategy is as easy as the following.
         X_training=X_training, y_training=y_training
     )
 
-For more details on how to implement your custom strategies, visit the
-page :ref:`Extending-modAL`!
+For more details on how to implement your custom strategies, visit the page `Extending modAL <content/overview/Extending-modAL.ipynb>`_!
 
 
 An example with active regression
@@ -195,27 +194,26 @@ Danka <https://www.tivadardanka.com>`__ (aka
    :maxdepth: 1
    :caption: Overview
 
-   modAL in a nutshell <content/overview/modAL-in-a-nutshell>
-   Installation <content/overview/Installation>
-   Extending modAL <content/overview/Extending-modAL>
+   content/overview/modAL-in-a-nutshell
+   content/overview/Installation
+   content/overview/Extending-modAL
 
 .. toctree::
    :maxdepth: 1
    :caption: Models
 
-   ActiveLearner <content/models/ActiveLearner>
-   BayesianOptimizer <content/models/BayesianOptimizer>
-   Committee <content/models/Committee>
-   CommitteeRegressor <content/models/CommitteeRegressor>
+   content/models/ActiveLearner
+   content/models/BayesianOptimizer
+   content/models/Committee
+   content/models/CommitteeRegressor
 
 .. toctree::
    :maxdepth: 1
    :caption: Query strategies
 
-   Acquisition functions <content/query_strategies/Acquisition-functions>
-   Uncertainty sampling <content/query_strategies/Uncertainty-sampling>
-   Disagreement sampling <content/query_strategies/Disagreement-sampling>
-   content/query_strategies/Ranked-batch-queries
+   content/query_strategies/Acquisition-functions
+   content/query_strategies/Uncertainty-sampling
+   content/query_strategies/Disagreement-sampling
 
 .. toctree::
    :maxdepth: 1
@@ -224,13 +222,12 @@ Danka <https://www.tivadardanka.com>`__ (aka
    content/examples/pool-based_sampling
    content/examples/ranked_batch_mode
    content/examples/Stream-based-sampling
-   Active regression <content/examples/active_regression>
-   Ensemble regression <content/examples/ensemble_regression>
+   content/examples/active_regression
+   content/examples/ensemble_regression
    content/examples/bayesian_optimization
    content/examples/Query-by-committee
    content/examples/Bootstrapping-and-bagging
-   content/examples/extending_modal
-   Keras integration <content/examples/Keras-integration>
+   content/examples/Keras-integration
 
 .. toctree::
    :glob: