diff --git a/README.md b/README.md
index 3588bbbae..bea77f163 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@ Use Keras if you need a deep learning library that:
 
 ## Guiding principles
 
-- __Modularity.__ A model is understood as a sequence of standalone, fully-configurable modules that can be plugged together with as little restrictions as possible. In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions and dropout are all standlone modules that you can combine to create new models. 
+- __Modularity.__ A model is understood as a sequence of standalone, fully-configurable modules that can be plugged together with as little restrictions as possible. In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions and dropout are all standalone modules that you can combine to create new models. 
 
 - __Minimalism.__ Each module should be kept short and simple (<100 lines of code). Every piece of code should be transparent upon first reading. No black magic: it hurts iteration speed and ability to innovate. 
 
@@ -255,7 +255,7 @@ Keras uses the following dependencies:
 
 ## Why this name, Keras?
 
-Keras (κέρας) means _horn_ in Greek. It is a reference to a literary image from ancient Greek and Latin literature, first found in the _Odyssee_, where dream spirits (_Oneiroi_, singular _Oneiros_) are divided between those who deceive men with false visions, who arrive to Earth through a gate of ivory, and those who anounce a future that will come to pass, who arrive through a gate of horn. It's a play on the words κέρας (horn) / κραίνω (fulfill), and ἐλέφας (ivory) / ἐλεφαίρομαι (deceive).
+Keras (κέρας) means _horn_ in Greek. It is a reference to a literary image from ancient Greek and Latin literature, first found in the _Odyssee_, where dream spirits (_Oneiroi_, singular _Oneiros_) are divided between those who deceive men with false visions, who arrive to Earth through a gate of ivory, and those who announce a future that will come to pass, who arrive through a gate of horn. It's a play on the words κέρας (horn) / κραίνω (fulfill), and ἐλέφας (ivory) / ἐλεφαίρομαι (deceive).
 
 Keras was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System).
 
diff --git a/keras/datasets/data_utils.py b/keras/datasets/data_utils.py
index 885dead05..8084e6712 100644
--- a/keras/datasets/data_utils.py
+++ b/keras/datasets/data_utils.py
@@ -30,10 +30,8 @@ def get_file(fname, origin, untar=False):
         progbar = None
 
     if untar:
-        if os.path.exists(untar_fpath):
-            pass
-        else:
-            print 'Unraring file...'
+        if not os.path.exists(untar_fpath):
+            print 'Untaring file...'
             tfile = tarfile.open(fpath, 'r:gz')
             tfile.extractall(path=datadir)
             tfile.close()
diff --git a/keras/models.py b/keras/models.py
index 4b1fd4162..99b7a6525 100644
--- a/keras/models.py
+++ b/keras/models.py
@@ -33,7 +33,7 @@ class Sequential(object):
         self.y_train = self.layers[-1].output(train=True)
         self.y_test = self.layers[-1].output(train=False)
 
-        Y = T.matrix() # ouput of model
+        Y = T.matrix() # output of model
         self.Y = Y
 
         train_loss = self.loss(self.Y, self.y_train)