Studies

Not recommending this as an introductory text. Ironically, what I like was how this book connects linear algebra to a variety of non-linear approaches such as neural networks, kernel PCA, etc.

The Good: Connecting many linear algebra concepts to their code implementations. Honestly the documentation for the np.linalg module might be a compelling linear algebra study blueprint in and out of itself. Intuitive explanations a...

Pros: Excellent problem set and the myriad examples of how linear algebra techniques can be applied to a variety of problems. The emphasis on the connections between linear algebra theory and problems such as KNN clustering (and also poi...

Excellent pedagogy and organization. Examples and the selection for the exercises really help, and the balance between mathematical rigor and accessibility is very well done. Gives Strang's books a run for their imo. Some gripes: 1. Woul...

* Very useful code snippets, practical tips and rules of thumb. * The intuition behind conformal prediction could use a bit more elaboration, but maybe that's not what the book is intended for. * They top-level survey of the relevant pa...