fix typo

Author: cezannec

README.md

@@ -24,7 +24,7 @@ There are also notebooks used as projects for the Nanodegree program. In the pro
 
 ### Recurrent Neural Networks
 
-* [Intro to Recurrent Networks (Time series & Character-level RNN)](https://github.com/udacity/deep-learning-v2-pytorch/tree/master/recurrent-neural-networks): Recurrent neural networks are able to use information about the sequence of data, such as the sequence of characters in text; learn how tom implement these in PyTorch for a variety of tasks.
+* [Intro to Recurrent Networks (Time series & Character-level RNN)](https://github.com/udacity/deep-learning-v2-pytorch/tree/master/recurrent-neural-networks): Recurrent neural networks are able to use information about the sequence of data, such as the sequence of characters in text; learn how to implement these in PyTorch for a variety of tasks.
 * [Embeddings (Word2Vec)](https://github.com/udacity/deep-learning-v2-pytorch/tree/master/word2vec-embeddings): Implement the Word2Vec model to find semantic representations of words for use in natural language processing.
 * [Sentiment Analysis RNN](https://github.com/udacity/deep-learning-v2-pytorch/tree/master/sentiment-rnn): Implement a recurrent neural network that can predict if the text of a moview review is positive or negative.
 * [Attention](https://github.com/udacity/deep-learning-v2-pytorch/tree/master/attention): Implement attention and apply it to annotation vectors.
@@ -160,4 +160,4 @@ cd deep-learning-v2-pytorch
 jupyter notebook
 ```
 
-To exit the environment when you have completed your work session, simply close the terminal window.
+To exit the environment when you have completed your work session, simply close the terminal window.