MASTERING TECHNICAL MATHEMATICS PB

MASTERING TECHNICAL MATHEMATICS PB
Author: Stan Gibilisco
Publisher: McGraw Hill Professional
Total Pages: 596
Release: 1999-06-20
Genre: Technology & Engineering
ISBN: 9780071378598

Boost our applied math skills--and rocket your career. Don't let weak or rusty applied math skills keep you from satisfying your technical career goals. Step by step -- and at your own pace--Mastering Technical Mathematics, Second Edition, by Stan Gibilisco and Norman Crowhurst, gives you the essential background you need to sharpen our algebra aptitude...wield quadratics...use mechanical math methods...perform trigonometry and geometry conversions...and harness the power of differentiation. You'll also get comfortable with calculus...learn to use complex quantities...apply logarithms...and more. Totally revised and updated with state-of-the-art coverage of logic and digital systems, this affordable expert tutor also provides helpful examples and illustrations, chapter self-tests--even a comprehensive final exam. It's the ideal prep tool for acing certification exams, earning a technical degree, or confidently tackling any engineering challenge.

Advanced Calculus (Revised Edition)

Advanced Calculus (Revised Edition)
Author: Lynn Harold Loomis
Publisher: World Scientific Publishing Company
Total Pages: 595
Release: 2014-02-26
Genre: Mathematics
ISBN: 9814583952

An authorised reissue of the long out of print classic textbook, Advanced Calculus by the late Dr Lynn Loomis and Dr Shlomo Sternberg both of Harvard University has been a revered but hard to find textbook for the advanced calculus course for decades.This book is based on an honors course in advanced calculus that the authors gave in the 1960's. The foundational material, presented in the unstarred sections of Chapters 1 through 11, was normally covered, but different applications of this basic material were stressed from year to year, and the book therefore contains more material than was covered in any one year. It can accordingly be used (with omissions) as a text for a year's course in advanced calculus, or as a text for a three-semester introduction to analysis.The prerequisites are a good grounding in the calculus of one variable from a mathematically rigorous point of view, together with some acquaintance with linear algebra. The reader should be familiar with limit and continuity type arguments and have a certain amount of mathematical sophistication. As possible introductory texts, we mention Differential and Integral Calculus by R Courant, Calculus by T Apostol, Calculus by M Spivak, and Pure Mathematics by G Hardy. The reader should also have some experience with partial derivatives.In overall plan the book divides roughly into a first half which develops the calculus (principally the differential calculus) in the setting of normed vector spaces, and a second half which deals with the calculus of differentiable manifolds.

Mastering Mathematica®

Mastering Mathematica®
Author: John W. Gray
Publisher: Academic Press
Total Pages: 667
Release: 2014-05-10
Genre: Mathematics
ISBN: 1483214036

Mastering Mathematica®: Programming Methods and Applications presents the mathematical results and turn them into precise algorithmic procedures that can be executed by a computer. This book provides insight into more complex situations that can be investigated by hand. Organized into four parts, this book begins with an overview of the use of a pocket calculator. This text then looks in more detail at numerical calculations and solving equations, both algebraic and differential equations. Other parts consider the built-in graphics and show how to make pictures without programming. This book discusses as well the four styles of programming, namely, functional programming, imperative programming, rewrite programing, and object oriented programming. The reader is also introduced to differentiable mapping to show the analysis of critical points of functions and the developments in differential geometry that are required to study minimal surfaces. This book is a valuable resource for graduate students in mathematics, mathematics education, engineering, and the sciences.

All of Statistics

All of Statistics
Author: Larry Wasserman
Publisher: Springer Science & Business Media
Total Pages: 446
Release: 2013-12-11
Genre: Mathematics
ISBN: 0387217363

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.

Probability and Statistics

Probability and Statistics
Author: Michael J. Evans
Publisher: Macmillan
Total Pages: 704
Release: 2004
Genre: Mathematics
ISBN: 9780716747420

Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.

Data Science and Machine Learning

Data Science and Machine Learning
Author: Dirk P. Kroese
Publisher: CRC Press
Total Pages: 538
Release: 2019-11-20
Genre: Business & Economics
ISBN: 1000730778

Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms
Author: David J. C. MacKay
Publisher: Cambridge University Press
Total Pages: 694
Release: 2003-09-25
Genre: Computers
ISBN: 9780521642989

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.