SETUP: a few text edits

SETUP.md

@@ -2,7 +2,8 @@
 
 In this guide we show how to setup all the dependencies to run the notebooks of this repo. 
 
-We have three different environments for our algorithms:
+Three environments are supported to run the notebooks in the repo:
+
 * Python CPU
 * Python GPU
 * PySpark
@@ -10,9 +11,9 @@ We have three different environments for our algorithms:
 ## Requirements
 
 - [Anaconda Python 3.6](https://conda.io/miniconda.html)
-- The library dependencies are generated depending on the environment we choose and can be found in this [script](scripts/generate_conda_file.sh).
-- Machine with GPU (optional).
-- Machine with Spark (optional).
+- The Python library dependencies can be found in this [script](scripts/generate_conda_file.sh).
+- Machine with Spark (optional for Python environment but mandatory for PySpark environment).
+- Machine with GPU (optional but desirable for computing acceleration).
 
 ## Conda environments
 
@@ -22,11 +23,11 @@ As a pre-requisite, we may want to make sure that Conda is up-to-date:
 
 We provided a script to [generate a conda file](scripts/generate_conda_file.sh), depending of the environment we want to use.
 
-To install each environment, first we need to generate a conda yml file and then install the environment. We can choose the environment name with the input `-n`. In the following examples, we provide a name example.
+To install each environment, first we need to generate a conda yml file and then install the environment. We can specify the environment name with the input `-n`. In the following examples, we provide a name example.
 
 ### Python CPU environment
 
-To install the Python CPU environment:
+Assuming the repo is cloned as `Recommenders` in the local system, to install the Python CPU environment:
 
     cd Recommenders
     ./scripts/generate_conda_file.sh
@@ -46,10 +47,9 @@ To install the PySpark environment, which by default installs the CPU environmen
 
     cd Recommenders
     ./scripts/generate_conda_file.sh --pyspark
-
     conda env create -n reco_pyspark -f conda_pyspark.yaml
 
-For this environment, we need to set the environment variables `PYSPARK_PYTHON` and `PYSPARK_DRIVER_PYTHON` to point to the conda python executable. 
+**NOTE** for this environment, we need to set the environment variables `PYSPARK_PYTHON` and `PYSPARK_DRIVER_PYTHON` to point to the conda python executable.
 
 For setting these variables every time the environment is activated, we can follow the steps of this [guide](https://conda.io/docs/user-guide/tasks/manage-environments.html#macos-and-linux). Assuming that we have installed the environment in `/anaconda/envs/reco_pyspark`, we create the file `/anaconda/envs/reco_pyspark/activate.d/env_vars.sh` and add: