.

Author: siyangimda

activelearning.rst

@@ -51,4 +51,5 @@ Of course, plateauing is determined on a good query strategy together with an ap
 Resources
 ----------
  * Active Learning Literature Survey. http://burrsettles.com/pub/settles.activelearning.pdf
- * Class Imbalance & Active Learning. https://pdfs.semanticscholar.org/7437/aae9bf347ab4ba4057f28df5f2eaf64d8fdc.pdf
+ * Class Imbalance & Active Learning. https://pdfs.semanticscholar.org/7437/aae9bf347ab4ba4057f28df5f2eaf64d8fdc.pdf
+ * Clustering: https://medium.com/towards-artificial-intelligence/how-to-use-active-learning-to-iteratively-improve-your-machine-learning-models-1c6164bdab99

reinforcement.rst

@@ -231,5 +231,6 @@ Rerun the game using the Q-table generated.
 Resources
 ----------
  * https://towardsdatascience.com/reinforcement-learning-implement-grid-world-from-scratch-c5963765ebff
+ * https://medium.com/swlh/introduction-to-reinforcement-learning-coding-q-learning-part-3-9778366a41c0
  * https://medium.com/@m.alzantot/deep-reinforcement-learning-demysitifed-episode-2-policy-iteration-value-iteration-and-q-978f9e89ddaa
  * https://medium.com/emergent-future/simple-reinforcement-learning-with-tensorflow-part-0-q-learning-with-tables-and-neural-networks-d195264329d0