Advise resources on un-supervised learning I have seen that people coming into data science will rush into scikit-learn or other libraries without trying to learn the knowledge behind. Its good to follow a top-down approach but most of times people don't go into depth, even if they do its in supervised-learning area. That't why I think un-supervised is neglected (or is it heavy influence of statistical inference). I would like to learn the un-supervised learning in-depth I tried some books so far (Sugiyama, Masashi - Introduction to Statistical Machine Learning-Morgan Kaufmann (2016) book) was better among others to build intuition around concepts.
If anyone have gone through same path and know other good reads or video tutorials kindly share in this thread.
I would recommend going through Towardsdatascience and Medium articles. They can explain the methods in a very simple and light way by summarizing the theory and also inlcuding the practical side of things.
for example: https://towardsdatascience.com/introduction-to-unsupervised-learning-8f1b189e9050
If you want to dive more into the maths the famous ESLII (Elements of Statiscal Learning) https://web.stanford.edu/~hastie/Papers/ESLII.pdf and Pattern Recognition  of Bishop (http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf) are the way to go. These two are the &quot;bible&quot; of Machine Learning