Download or read book Linear Algebra Crash Course Black and White written by Wesolvethem and published by Createspace Independent Publishing Platform. This book was released on 2017-03-08 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Free math and physics resources via JonathanTullis.com My formula sheets and crash course books are designed to assist college students throughout their STEM degree. I have isolated all of the most important information from all previous courses, current courses, and future courses that STEM majors must take i.e. Algebra, Trigonometry, PreCalculus, Calculus (all areas), Linear Algebra, Differential Equations, Physics and more.
Download or read book Linear Algebra Crash Course Detailed Solutions for the Most Common Linear Algebra Problems written by Wesolvethem Team and published by Independently Published. This book was released on 2017-08-05 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detailed solutions for the most common linear algebra problems.
Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Download or read book Introduction to Linear Algebra and Differential Equations written by John Warren Dettman and published by McGraw-Hill Companies. This book was released on 1974 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excellent introductory text focuses on complex numbers, determinants, orthonormal bases, symmetric and hermitian matrices, first order non-linear equations, linear differential equations, Laplace transforms, Bessel functions, more. Includes 48 black-and-white illustrations. Exercises with solutions. Index.
Download or read book A First Course in Linear Algebra written by Raymond A. Beauregard and published by . This book was released on 1973 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A First Course in Linear Algebra written by Daniel Zelinsky and published by . This book was released on 1968 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Manga Guide to Linear Algebra written by Shin Takahashi and published by National Geographic Books. This book was released on 2012-05-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reiji wants two things in life: a black belt in karate and Misa, the girl of his dreams. Luckily, Misa's big brother is the captain of the university karate club and is ready to strike a deal: Reiji can join the club if he tutors Misa in linear algebra. Follow along in The Manga Guide to Linear Algebra as Reiji takes Misa from the absolute basics of this tricky subject through mind-bending operations like performing linear transformations, calculating determinants, and finding eigenvectors and eigenvalues. With memorable examples like miniature golf games and karate tournaments, Reiji transforms abstract concepts into something concrete, understandable, and even fun. As you follow Misa through her linear algebra crash course, you'll learn about: –Basic vector and matrix operations such as addition, subtraction, and multiplication –Linear dependence, independence, and bases –Using Gaussian elimination to calculate inverse matrices –Subspaces, dimension, and linear span –Practical applications of linear algebra in fields like computer graphics, cryptography, and engineering But Misa's brother may get more than he bargained for as sparks start to fly between student and tutor. Will Reiji end up with the girl—or just a pummeling from her oversized brother? Real math, real romance, and real action come together like never before in The Manga Guide to Linear Algebra.
Download or read book Basics of Linear Algebra for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-01-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.
Download or read book Computational Physics written by Darren Walker and published by Mercury Learning and Information. This book was released on 2022-01-17 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated edition provides an introduction to computational physics in order to perform physics experiments on the computer. Computers can be used for a wide variety of scientific tasks, from the simple manipulation of data to simulations of real-world events. This book is designed to provide the reader with a grounding in scientific programming. It contains many examples and exercises developed in the context of physics problems. The new edition now uses C++ as the primary language. The book covers topics such as interpolation, integration, and the numerical solutions to both ordinary and partial differential equations. It discusses simple ideas, such as linear interpolation and root finding through bisection, to more advanced concepts in order to solve complex differential equations. It also contains a chapter on high performance computing which provides an introduction to parallel programming. FEATURES: Includes some advanced material as well as the customary introductory topics Uses a comprehensive C++ library and several C++ sample programs ready to use and build into a library of scientific programs Features problem-solving aspects to show how problems are approached and to demonstrate the methods of constructing models and solutions
Download or read book A First Course in Linear Algebra written by Hal G. Moore and published by Addison-Wesley Longman. This book was released on 1992 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book No Bullshit Guide to Linear Algebra written by Ivan Savov and published by . This book was released on 2020-10-25 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook covers the material for an undergraduate linear algebra course: vectors, matrices, linear transformations, computational techniques, geometric constructions, and theoretical foundations. The explanations are given in an informal conversational tone. The book also contains 100+ problems and exercises with answers and solutions. A special feature of this textbook is the prerequisites chapter that covers topics from high school math, which are necessary for learning linear algebra. The presence of this chapter makes the book suitable for beginners and the general audience-readers need not be math experts to read this book. Another unique aspect of the book are the applications chapters (Ch 7, 8, and 9) that discuss applications of linear algebra to engineering, computer science, economics, chemistry, machine learning, and even quantum mechanics.
Download or read book Linear Algebra written by Kenneth Hoffman and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Download or read book Linear Algebra written by Kuldeep Singh and published by Oxford University Press. This book was released on 2013-10 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is intended for first- and second-year undergraduates arriving with average mathematics grades ... The strength of the text is in the large number of examples and the step-by-step explanation of each topic as it is introduced. It is compiled in a way that allows distance learning, with explicit solutions to all of the set problems freely available online http://www.oup.co.uk/companion/singh" -- From preface.
Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Download or read book The Software Encyclopedia written by and published by . This book was released on 1997 with total page 1586 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Math and Architectures of Deep Learning written by Krishnendu Chaudhury and published by Simon and Schuster. This book was released on 2024-03-26 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. You'll peer inside the "black box" to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. Math and Architectures of Deep Learning sets out the foundations of DL usefully and accessibly to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems.
