Further reading

• The 5 Clustering Algorithms Data Scientists Need to Know: https://towardsdatascience.com/the-5-clustering-algorithms-data-scientists-need-to-know-a36d136ef68
• Clustering: https://scikit-learn.org/stable/modules/clustering.html
• Different Types of Clustering Algorithm: https://www.geeksforgeeks.org/different-types-clustering-algorithm/
• An Introduction to Clustering and different methods of clustering: https://www.analyticsvidhya.com/blog/2016/11/an-introduction-to-clustering-and-different-methods-of-clustering/
• Graph theory introductory book: Graph Theory (Graduate Texts in Mathematics) by Adrian Bondy and U.S.R. Murty.
• This book covers a lot of aspects of ML theory and algorithms: The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman