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+[Quantum ML Algorithms Historical Perspective](https://www.chemicalqdevice.com/quantum-ml-algorithms-historical-perspective) PDF 7/31/23.
+
+Synopsis: An early paper to learn Quantum ML basics, as well as some of the common
+quantum models being researched. <br>
+
+1) Emerging Quantum ML Models <br>
+A) Quantum Support Vector Machine <br> 
+a) Evaluation of an inner product is better on a quantum computer <br> 
+B) Quantum K-Nearest Neighbor Methods <br>
+a) Efficient calculation of classical distances with quantum computer <br>
+C) K-Means Quantum Clustering <br>
+a) Several full quantum routines for clustering are available <br>
+D) Quantum Decision Trees <br>
+a) Quantum feature states encode n features into quantum system <br>
+E) Quantum State Classification with Bayesian Methods <br>
+a) Reformulation in the language of open quantum systems <br>
+F) Hidden Quantum Markov Models <br>
+a) Contain classical models and richer generalization dynamics <br>
+G) Quantum Neural Networks <br>
+a) Quantum dots; adiabatic computing; hopfield networks; fuzzy ff <br>