Fix typos in docs.

azavea · Oct 18, 2018 · 6c8957b · 6c8957b
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diff --git a/docs/conf.py b/docs/conf.py
@@ -85,7 +85,7 @@
         ProjectLink('Documentation TOC', 'index.html#documentation'),
         ProjectLink('API Reference TOC', 'index.html#api-reference'),
         ProjectLink('Project Website', 'https://rastervision.io/'),
-        ProjectLink('PyPI releases', 'https://pypi.org/project/raster-vision/'),
+        ProjectLink('PyPI releases', 'https://pypi.org/project/rastervision/'),
         ProjectLink('GitHub', 'https://github.com/azavea/raster-vision'),
         ProjectLink('Gitter Channel', 'https://gitter.im/azavea/raster-vision'),
         ProjectLink('Raster Vision Examples', 'https://github.com/azavea/raster-vision-examples'),

diff --git a/docs/experiments.rst b/docs/experiments.rst
@@ -37,7 +37,7 @@ In the ``tiny_spacenet.py`` example from the :ref:`quickstart`, the ``TinySpacen
 ExperimentConfig
 ----------------
 
-An experiment a sequence of commands that represents a machine learning workflow.
+An experiment is a sequence of commands that represents a machine learning workflow.
 The way those workflows are configured is by constructing an ``ExperimentConfig``.
 An ``ExperimentConfig`` is what is returned from the experiment methods of an ``ExperimentSet``,
 and are used by Raster Vision to determine what and how :ref:`commands` will be run. While the

diff --git a/docs/index.rst b/docs/index.rst
@@ -22,7 +22,7 @@ Raster Vision workflows begin when you have a set of images and training data,
 optionally with Areas of Interest (AOIs) that describe where the images are labeled. Raster Vision
 workflows end with a packaged model and configuration that allows you to
 easily utilize models in various  deployment situations. Inside the Raster Vision
-workflow, there's the proccess of running multiple experiments to find the best model
+workflow, there's the process of running multiple experiments to find the best model
 or models to deploy.
 
 .. image:: _static/overview-raster-vision-workflow.png

diff --git a/docs/setup.rst b/docs/setup.rst
@@ -36,7 +36,7 @@ If you'd like to use AWS, Tensorflow and/or Keras with Raster Vision, you can in
 
 .. code-block:: console
 
-    > pip install rastrevision[aws,tensorflow,tensorflow-gpu]
+    > pip install rastervision[aws,tensorflow,tensorflow-gpu]
 
 If you'd like to use Raster Vision with `Tensorflow Object Detection <https://github.com/tensorflow/models/tree/master/research/object_detection>`_ or `TensorFlow DeepLab <https://github.com/tensorflow/models/tree/master/research/deeplab>`_, you'll need to follow the instructions in thier documentation about how to install, or look at our Dockerfile to see an example of setting this up.