From fe9982cdb7bb9ce9b21f603867111b659d054949 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Dar=C3=ADo=20Here=C3=B1=C3=BA?= <magallania@gmail.com>
Date: Thu, 3 Dec 2020 18:48:38 -0300
Subject: [PATCH] Minor proposal (line 77)

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index cdd2dd75..d5c12e55 100755
--- a/README.md
+++ b/README.md
@@ -74,12 +74,12 @@ If you use the data files I've linked above, those are quite large, and will tak
 Playlist.ipynb is a simple Jupyter Notebook which creates a nicely formatted playlist for listening to all the generations.
 <h2>Music Critic:</h2>
 <ul>
-  <li>make_critic_data.py - create the training and test datasests (requires a trained generation model to create the fake data)</li>
+  <li>make_critic_data.py - create the training and test datasets (requires a trained generation model to create the fake data)</li>
   <li>critic.py - trains a classifier to predict if a sample is human-composed or LSTM-composed
 </ul>
 <h2>Composer Classifier:</h2>
 <ul>
-  <li>make_composer_data.py - create the training and test datasests (all from human composed pieces)</li>
+  <li>make_composer_data.py - create the training and test datasets (all from human composed pieces)</li>
   <li>composer_classifier.py - trains a classifier to predict which human composed the piece
 </ul>