Book picks similar to
Queueing Systems, Volume 1: Theory by Leonard Kleinrock


math
non-fiction
mathematics
books-i-want-but-don-t-have

Who Is Fourier? a Mathematical Adventure


Transnational College of Lex - 1995
    This is done in a way that is not only easy to understand, but is actually fun! Professors and engineers, with high school and college students following closely, comprise the largest percentage of our readers. It is a must-have for anyone interested in music, mathematics, physics, engineering, or complex science. Dr. Yoichiro Nambu, 2008 Nobel Prize Winner in Physics, served as a senior adviser to the English version of Who is Fourier? A Mathematical Adventure.

Information Theory, Inference and Learning Algorithms


David J.C. MacKay - 2002
    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook 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. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in 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, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

Introductory Statistics with R


Peter Dalgaard - 2002
    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

Structure and Interpretation of Computer Programs


Harold Abelson - 1984
    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

Introduction to Graph Theory


Richard J. Trudeau - 1994
    This book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, more. Includes exercises. 1976 edition.

Firing A Rocket : Stories of the Development of the Rocket Engines for the Saturn Launch Vehicles and the Lunar Module as Viewed from the Trenches (Kindle Single)


James R. French - 2017
    But Neil Armstrong and Sally Ride would have never made history, and humankind would not have touched the stars, if not for the men and women on the ground who lit the fuse that launched the first rockets.Enthralled as a boy by the exploits of Flash Gordon and the novels of Robert Heinlein and Arthur C. Clarke—who put the science in science fiction—James French became one of the original unsung engineers of America’s groundbreaking space program. His fascinating memoir offers an up-close-and-technical look at building, testing, and perfecting the pioneering Saturn rockets and original lunar landing module, and he shares true tales, both humorous and harrowing, of life—and near death—on the front lines of scientific exploration.If you’ve ever said, “It’s not rocket science,” you’re right. It’s rocket engineering—and here’s your chance to marvel at how it changed the world and made it possible to explore all that lies beyond Earth. James R French graduated from MIT in 1958 with a degree of BSME Specializing in Propulsion. His first job was with Rocketdyne Division of North American Aviation where he worked on developmental testing of H-1 engines and combustion devices hardware for F-1 and J-2 engines used in Saturn 5. Mr. French has also worked at TRW Systems, where he was Lead Development Test Engineer on the Lunar Module Descent Engine, and Jet Propulsion Laboratory where he was Advanced Planetary studies Manager as well as Chief Engineer for the SP-100 Space Nuclear Power System and worked on Mariners 5, 6, 7, 8, and 9; Viking 1 & 2 and Voyager 1 & 2. . In 1986, he helped found American Rocket Co., a commercial launch company.Since 1987, Mr. French has been consultant to a variety of aerospace companies, SDIO, NASA, and USAF. He has participated in various startup companies in the private space flight arena and currently consults extensively to Blue Origin. Mr. French is co-author with Dr. Michael Griffin of the best-selling text Space Vehicle Design, published by AIAA. The second edition of the book has received the Summerfield Book Award for 2008. Mr. French is a Fellow of both AIAA and the British Interplanetary Society and a 50+ year member of AIAA. He has held several Technical Committee and other posts in AIAA. Cover design by Evan Twohy

Calculus


Dale E. Varberg - 1999
    Covering various the materials needed by students in engineering, science, and mathematics, this calculus text makes effective use of computing technology, graphics, and applications. It presents at least two technology projects in each chapter.

Infinite Powers: How Calculus Reveals the Secrets of the Universe


Steven H. Strogatz - 2019
    We wouldn’t have unraveled DNA or discovered Neptune or figured out how to put 5,000 songs in your pocket. Though many of us were scared away from this essential, engrossing subject in high school and college, Steven Strogatz’s brilliantly creative, down‑to‑earth history shows that calculus is not about complexity; it’s about simplicity. It harnesses an unreal number—infinity—to tackle real‑world problems, breaking them down into easier ones and then reassembling the answers into solutions that feel miraculous. Infinite Powers recounts how calculus tantalized and thrilled its inventors, starting with its first glimmers in ancient Greece and bringing us right up to the discovery of gravitational waves (a phenomenon predicted by calculus). Strogatz reveals how this form of math rose to the challenges of each age: how to determine the area of a circle with only sand and a stick; how to explain why Mars goes “backwards” sometimes; how to make electricity with magnets; how to ensure your rocket doesn’t miss the moon; how to turn the tide in the fight against AIDS. As Strogatz proves, calculus is truly the language of the universe. By unveiling the principles of that language, Infinite Powers makes us marvel at the world anew.

Storytelling with Data: A Data Visualization Guide for Business Professionals


Cole Nussbaumer Knaflic - 2015
    You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!

Machine Learning


Ethem Alpaydin - 2016
    It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

Paradox: The Nine Greatest Enigmas in Physics


Jim Al-Khalili - 2012
    A fun and fascinating look at great scientific paradoxes.   Throughout history, scientists have come up with theories and ideas that just don't seem to make sense.  These we call paradoxes.  The paradoxes Al-Khalili offers are drawn chiefly from physics and astronomy and represent those that have stumped some of the finest minds.  For example, how can a cat be both dead and alive at the same time?  Why will Achilles never beat a tortoise in a race, no matter how fast he runs?  And how can a person be ten years older than his twin?   With elegant explanations that bring the reader inside the mind of those who've developed them, Al-Khalili helps us to see that, in fact, paradoxes can be solved if seen from the right angle.  Just as surely as Al-Khalili narrates the enduring fascination of these classic paradoxes, he reveals their underlying logic.  In doing so, he brings to life a select group of the most exciting concepts in human knowledge.  Paradox is mind-expanding fun.

Discovering Statistics Using SPSS (Introducing Statistical Methods)


Andy Field - 2000
    What's new in the Second Edition? 1. Fully compliant with the latest version of SPSS version 12 2. More coverage of advanced statistics including completely new coverage of non-parametric statistics. The book is 50 per cent longer than the First Edition. 3. Each section of each chapter now has a notation - 1,2 or 3 - referring to the intended level of study. This helps students navigate their way through the book and makes it user-friendly for students of ALL levels. 4. Has a 'how to use this book' section at the start of the text. 5. Characters in each chapter have defined roles - summarizing key points, to pose questions etc 6. Each chapter now has several examples for students to work through. Answers provided on the enclosed CD-ROM

Database Design for Mere Mortals: A Hands-On Guide to Relational Database Design


Michael J. Hernandez - 1996
    You d be up to your neck in normal forms before you even had a chance to wade. When Michael J. Hernandez needed a database design book to teach mere mortals like himself, there were none. So he began a personal quest to learn enough to write one. And he did.Now in its Second Edition, Database Design for Mere Mortals is a miracle for today s generation of database users who don t have the background -- or the time -- to learn database design the hard way. It s also a secret pleasure for working pros who are occasionally still trying to figure out what they were taught.Drawing on 13 years of database teaching experience, Hernandez has organized database design into several key principles that are surprisingly easy to understand and remember. He illuminates those principles using examples that are generic enough to help you with virtually any application.Hernandez s goals are simple. You ll learn how to create a sound database structure as easily as possible. You ll learn how to optimize your structure for efficiency and data integrity. You ll learn how to avoid problems like missing, incorrect, mismatched, or inaccurate data. You ll learn how to relate tables together to make it possible to get whatever answers you need in the future -- even if you haven t thought of the questions yet.If -- as is often the case -- you already have a database, Hernandez explains how to analyze it -- and leverage it. You ll learn how to identify new information requirements, determine new business rules that need to be applied, and apply them.Hernandez starts with an introduction to databases, relational databases, and the idea and objectives of database design. Next, you ll walk through the key elements of the database design process: establishing table structures and relationships, assigning primary keys, setting field specifications, and setting up views. Hernandez s extensive coverage of data integrity includes a full chapter on establishing business rules and using validation tables.Hernandez surveys bad design techniques in a chapter on what not to do -- and finally, helps you identify those rare instances when it makes sense to bend or even break the conventional rules of database design.There s plenty that s new in this edition. Hernandez has gone over his text and illustrations with a fine-tooth comb to improve their already impressive clarity. You ll find updates to reflect new advances in technology, including web database applications. There are expanded and improved discussions of nulls and many-to-many relationships; multivalued fields; primary keys; and SQL data type fields. There s a new Quick Reference database design flowchart. A new glossary. New review questions at the end of every chapter.Finally, it s worth mentioning what this book isn t. It isn t a guide to any specific database platform -- so you can use it whether you re running Access, SQL Server, or Oracle, MySQL or PostgreSQL. And it isn t an SQL guide. (If that s what you need, Michael J. Hernandez has also coauthored the superb SQL Queries for Mere Mortals). But if database design is what you need to learn, this book s worth its weight in gold. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

Practical Statistics for Data Scientists: 50 Essential Concepts


Peter Bruce - 2017
    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

Linear Algebra and Its Applications [with CD-ROM]


David C. Lay - 1993