The author tries, in all moment, to demonstrate that linear algebra is a fascinating subject by showing both, its beauty and value. Due to its large file size, this book may take longer to download. However, the writing is often unclear and bars understanding - which is a shame. A variety of interesting examples and exercises in each chapter will help you to understand and manipulate the objects of linear algebra. It’s written in a very didactical way, so it’s suitable for self-study. The text also includes several exercises, which seem perfectly targeted for each section. Klein was born and raised in Berkeley, California. His favorite xkcd is 612. Examples and exercises are provided throughout the book. Does this book contain inappropriate content? In this class, you will learn the concepts and methods of linear algebra, and how to use them to think about problems arising in computer science. 1. Reviewed in the United States on August 12, 2015. It is designed both for engineering and science majors, but has enough abstraction to be useful for potential math majors. Each section ends with a set of exercises where students must prove their acquired knowledge. Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares, Linear Algebra Done Right (Undergraduate Texts in Mathematics), Algorithms Illuminated (Part 4): Algorithms for NP-Hard Problems, Algorithms Illuminated (Part 3): Greedy Algorithms and Dynamic Programming, Linear Algebra and Optimization for Machine Learning: A Textbook. I did not enroll in the course but instead bought the book for self study at some stage. His love for computer science has never abated, but in a chance encounter with E. W. Dijkstra in 1979, he was told that, if he wanted to do computer science, he had better learn some math. Behind all the matrices, polynomials, vectors and spaces, there is a fascinating subject which tools can help you to solve many practical problems. Professor Klein does much of it with this book. Welcome to Linear Algebra for Beginners: Open Doors to Great Careers. The Kindle version is not the same as recent printed versions and contains errors long since corrected in the print format. June 11, 2014. Linear Algebra A free Linear Algebra Textbook and Online Resource. This book is quite different in its approach because it spends a lot of time providing the intuition behind fundamental concepts. You miss the four textbooks which are better than all the above, namely, (1) Linear Algebra (Hoffman and Kunze), (2) Linear Algebra (Spielberg and Spence, (3) Finite-Dimensional Vector Spaces (Halmos, this is the all-time classic, esp. And yet, it took me years on the job to relate the books to the problems we were solving. The book is written in a very colloquial and natural way, using an informal and personal style, and emphasizing on understanding instead on proofs; nevertheless it does not flow as easily as the author’s lectures. Please try again. I am am a retired software engineer who spent my entire career working for an aero-space research company. It is comical. This shopping feature will continue to load items when the Enter key is pressed. Mathematical concepts and computational problems are motivated by applications in computer science. Do you believe that this item violates a copyright? Throughout the book, significant motivating examples are woven into the text, which help students to appreciate the utility and beauty of these subjects as well as the mechanics. Linear Algebra is a topic connected to different fields inside and outside mathematics like functional analysis, differential equations, engineering, graph theory, statistics, linear programming, and computer graphics. In addition to Python code examples, the book also distinguishes itself through the use of example scenarios that are meaningful to computing students. The reader learns by doing, writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Each chapter begins with clear statements of pertinent definitions, principles and theorems together with illustrative and other descriptive material. On each section, the author presents a brief, but useful discussion on real world applications. Linear Algebra is a topic connected to different fields inside and outside mathematics like functional analysis, differential equations, engineering, graph theory, statistics, linear programming, and computer graphics. From a pedagogical point of view, the book is excellent, and it will be found helpful to all readers regardless of their fields of specialization. I rarely write book reviews but I am compelled to write one for Coding the Matrix. S ome of the very best books on Machine learning were released online for free. It is a full presentation that will give you an intuitive grasp of linear algebra from both, the geometric and algebraic points of view, and will capture your attention until the end of the book. Numerous proofs of theorems are included among the solved problems. If you take the time to work through this book, you will be a master of the topic with a much wider foundation and with many different approaches to same problem. An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Behind all the matrices, polynomials, vectors and spaces, there is a fascinating subject which tools can help you to solve many practical problems. Photo by Mads Schmidt Rasmussen on Unsplash. Used to be the go textbooks for IITJEE, INdi. Throughout the book, the theory is motivated and reinforced by genuine applications, allowing pure mathematicians to teach applied mathematics. To show a simple example, it is impossible to develop graphic software applications like photo editors or graphical games without a good understanding of this topic. The book includes challenge problems to complement the review problems that have been highly praised in previous editions. Reviewed in the United Kingdom on August 29, 2013. Klein received a B.A. To demonstrate how linear algebra can be applied in different fields of science, the author presents several applications, and many examples and exercises make reference to different disciplines. This review is specific to the Kindle version of the book. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. What is the intuition behind a Matrix? The basic course is followed by seven applications: differential equations, engineering, graph theory, statistics, Fourier methods and the Fast Fourier Transform, linear programming, and computer graphics. To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. The order used to present the books is not relevant. Linear algebra Books. This book contains 3000 Solved Problems that can not only help students to understand abstract concepts of linear algebra, but they are also, an excellent complement for any course of Linear Algebra. I deeply regret not having it back then. The index is both skimpy and inaccurate. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. I found this book invaluable while taking the author's course Coding the Matrix on coursera.org. There are hundreds of books with the aim of teaching Linear Algebra, your choice will depend, basically, on the kind of course you are taking, and on the approach, prose and rigor of the text you prefer to study. To get the free app, enter your mobile phone number. Theoretical developments are always accompanied with detailed examples, and each section ends with a large number of carefully chosen exercises from which the students can gain further insight. The rst three or four chapters can stand alone as a one semester course in abstract algebra. Linear Algebra is not what it seems at first thought. It is rife with typos, some of which could mislead readers not already familiar with linear algebra. Linear Algebra course+book recommendation for computer science? Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. Thousands of teachers in colleges and universities and now high schools are using this book, which truly explains this crucial subject.

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