corrected a typo

README.md

@@ -70,7 +70,7 @@ There are many RL tutorials, courses, papers in the internet. This one summarize
 
 
 ## What is RL? <a name="whatisRL"></a>
-Machine learning mainly consists of three methods: Supervised Learning, Unsupervised Learning and Reinforcement Learning. Supervised Learning provides mapping functionality between input and output using labelled dataset. Some of the supervised learning methods: Linear Regression, Support Vector Machines, Neural Networks, etc. Unsupervised Learning provides grouping and clustering functionality. Some of the supervised learning methods: K-Means, DBScan, etc. Reinforcement Learning is different from supervised and unsupervised learning. RL provides behaviour learning. 
+Machine learning mainly consists of three methods: Supervised Learning, Unsupervised Learning and Reinforcement Learning. Supervised Learning provides mapping functionality between input and output using labelled dataset. Some of the supervised learning methods: Linear Regression, Support Vector Machines, Neural Networks, etc. Unsupervised Learning provides grouping and clustering functionality. Some of the unsupervised learning methods: K-Means, DBScan, etc. Reinforcement Learning is different from supervised and unsupervised learning. RL provides behaviour learning. 
 
 "A reinforcement learning algorithm, or agent, learns by interacting with its environment. The agent receives rewards by performing correctly and penalties for performing incorrectly. The agent learns without intervention from a human by maximizing its reward and minimizing its penalty" [*](https://www.techopedia.com/definition/32055/reinforcement-learning). RL agents are used in different applications: Robotics, self driving cars, playing atari games, managing investment portfolio, control problems. I am believing that like many AI laboratories do, reinforcement learning with deep learning will be a core technology in the future.