Added reference to Q81. (#2561)

Ebazhanov · Oct 27, 2021 · 0f5af6d · 0f5af6d
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@@ -621,6 +621,9 @@ Note: there are centres of clusters (C0, C1, C2).
 - [ ] a type of reinforcement learning where accuracy degrades over time
 - [x] a type of reinforcement learning that focuses on rewards
 
+**Explanation**:Q-learning is a model-free reinforcement learning algorithm.Q-learning is a values-based learning algorithm. Value based algorithms updates the value function based on an equation(particularly Bellman equation).
+[Reference](https://towardsdatascience.com/a-beginners-guide-to-q-learning-c3e2a30a653c#:~:text=Q%2Dlearning%20is%20a%20model,equation(particularly%20Bellman%20equation).&text=Means%20it%20learns%20the%20value,independently%20of%20the%20agent's%20actions.)
+
 #### Q82. Data in your model has low bias and low variance. How would you expect the data points to be grouped together on the diagram?
 
 - [ ] They would be grouped tightly together in the predicted outcome.