Linear Algebra and Learning from Data

A good guide to linear algebra in machine learning but the material is not always well organised. The introductory section (a quarter of the book) covers a lot ground but don’t expect to be able to learn linear algebra from scratch as various aspects are omitted or only mentioned in passing.

Well done, very clear and explain in details .

Any book by Prof Strang, is a book worth owning. If you have an interest in an area of study that Prof Strang has written a textbook about, just buy his book and learn it cold. 'Linear Algebra and Learning from Data' is another ringer.

Gilbert Strang, well known MIT professor and author, writes another book on Linear algebra. He put a lot of effort into making the material accessible and not assuming a background in linear algebra (matrices) so aimed at beginners. There is a bit of 'personal commentary' added to the text that is trying to make the public comfortable that wouldn't normally be in a text book but doesn't bother me much here. The added focus is on applications to Machine learning and other data extraction so it focuses on linear algebra that are useful for that purpose and how they are useful.

Il miglior libro sulle applicazioni dell’Algebra Lineare alla data science

Uso esse produto em minhas pesquisas acadêmicas.