Linear Algebra and Learning from Data by Gilbert Strang - PDF free download eBook
Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of...
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Details of Linear Algebra and Learning from Data
- Exact title of the book
- Linear Algebra and Learning from Data
- Book author
- Gilbert Strang
- Book edition
- Number of pages
- 446 pages
- February 28th 2019 by Wellesley College
- File size (in PDF)
- 1784 kB
Some brief overview of book
Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data.
Included are: the four fundamental subspaces, singular value decompositions, special marices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.