├── AppliedLinearAlgebra.pdf └── README.md /AppliedLinearAlgebra.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/huynguyen250896/Introduction-to-Applied-Linear-Algebra/9d0a7b3d5d2814ad15e1976aebf2a2595a9e6643/AppliedLinearAlgebra.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares - Stephen Boyd & Lieven Vandenberghe 2 |
I've been summarizing this book which you can read the online version of the book: http://vmls-book.stanford.edu/vmls.pdf 3 |
the book provides enough knowledge of Linear algebra and its applications that equips us with crucial tools to deeply dig into Machine Learning/ Deep learning in the view of mathematicians
Besides, if you are of interest to online learning courses, I will recommend you to refer to [MIT 18.06 video lectures](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8), or even its newer version [MIT 18.065 video lectures](https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/). To grasp the knowledge well, in addition to doing the assignments with [solutions](http://math.mit.edu/~gs/linearalgebra/) from a book named 'INTRODUCTION TO LINEAR ALGEBRA' (5th edition 2016) of Prof. Gilbert Strang attached with the MIT video lectures, you can additionally see [Math 110. Linear Algebra](https://math.berkeley.edu/~mcivor/math110su13/). It doesn't have video lectures but it has more assignments with solutions so you can practice even more. 4 | --------------------------------------------------------------------------------