fix doc

Author: yomguy

docs/source/core_api/index.rst

@@ -2,6 +2,9 @@
 Core API
 =================
 
+Introduction
+=============
+
 TimeSide is first a python framework enabling low and high level audio analysis, imaging, transcoding, streaming and labelling. Its high-level API is designed to enable complex processing on very large datasets of any audio or video assets with a plug-in architecture, a secure scalable backend and an extensible dynamic web frontend. Some usecases: scaled audio computing (filtering, machine learning, etc), web audio visualization, audio process prototyping, realtime and on-demand transcoding and streaming over the web, automatic segmentation and labelling synchronized with audio events
 
 Because there are a lot of tools available in the Python ecosystem dedicated to music information retrieval, machine learning and data analysis, we have decided to embed all main ones: Aubio, Yaafe, Essentia, VAMP, librosa, GStreamer, TensorFlow, Torch, PyTorch, scikit-learn, Jupyter, Pandas and Pytables. They are used to develop native TimeSide plugins though its simple processing API.
@@ -16,7 +19,6 @@ The following diagram shows and example of a pipe.
 .. image:: ../images/TimeSide_pipe.svg
   :width: 800 px
 
-
 Classes
 ========
 

docs/source/development.rst

@@ -2,7 +2,7 @@
 Development
 ===========
 
-First, setup the composition environment at the root of the project:
+First, setup the composition environment at the root of the project::
 
     echo "COMPOSE_FILE=docker-compose.yml:env/debug.yml" > .env
 

docs/source/production.rst

@@ -2,7 +2,7 @@
 Production
 ===========
 
-First, setup the composition environment at the root of the project:
+First, setup the composition environment at the root of the project::
 
     echo "COMPOSE_FILE=docker-compose.yml:env/prod.yml" > .env