Morris Mano, Charles R. Kime - Prentice Hall (2007) - Hardback - 678 pages - ISBN 013198926XFeaturing a strong emphasis on the fundamentals underlying contemporary logic design using hardware description languages, synthesis, and verification, this book focuses on the ever-evolving applications of basic computer design concepts with strong connections to real-world technology.Treatment of logic design, digital system design, and computer design.Ideal for self-study by engineers and computer scientists.

    An extensive subject review covers the following general areas: Foundations of World Civilization (8000 B.C.–1000 A.D.) World Cultures Maturing (1000–1450) World Cultures Interacting (1450–1750) World Cultures in the Modern Era (1750–1914) The 20th Century and Contemporary World Cultures (1914–2009)

    But if you haven't seen the performance improvements you expected, or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you'll also learn how to make it sing.With this book, you'll explore:How Spark SQL's new interfaces improve performance over SQL's RDD data structureThe choice between data joins in Core Spark and Spark SQLTechniques for getting the most out of standard RDD transformationsHow to work around performance issues in Spark's key/value pair paradigmWriting high-performance Spark code without Scala or the JVMHow to test for functionality and performance when applying suggested improvementsUsing Spark MLlib and Spark ML machine learning librariesSpark's Streaming components and external community packages

     Or build long term income streams that you enjoy and that allow you to finally #ClaimYourFREEDOM® and leave that dreary 9-5 job once and for all. PART 1 starts with the Best Places to Find Jobs to Work from Home grouped by skill and experience level: Basic Skills Intermediate Skills PRO Skills College Degree Required This is followed by a number of flexible job options in your local area as well as how and where to find jobs fast. Next, you'll find several innovative ways to monetize your home and car (and no - not just Uber & AirBnB....). Then we get to the first list of Top Home-Based Business Opportunities, some with significant income potential - even on a part time basis. PART 2 lists more home-based job and business ideas grouped by your interests, passions and hobbies: Pets Travel (local) Arts & Crafts Writing Photo + Video Fashion Cooking Health & Wellness Gardening Kids

    Stop and smell the tulips as you hike past whirring windmills. Visit the ultramodern European Parliament. Explore beyond the cosmopolitan bustle of Brussels with trips to Ghent and Antwerp. When it’s time for a break, sample fine chocolates or sip local beers—each served in its own distinctive glass.Rick’s candid, humorous advice will guide you to good-value hotels and restaurants. He’ll help you plan where to go and what to see, depending on the length of your trip. You’ll get up-to-date recommendations about what is worth your time and money. More than just reviews and directions, a Rick Steves guidebook is a tour guide in your pocket.This first edition guide replaces Rick Steves' Snapshot Bruges & Brussels, ISBN 9781612382296.

    This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to - Use the scientific method to evaluate hypotheses using controlled experiments - Define key metrics and ideally an Overall Evaluation Criterion - Test for trustworthiness of the results and alert experimenters to violated assumptions - Build a scalable platform that lowers the marginal cost of experiments close to zero - Avoid pitfalls like carryover effects and Twyman's law - Understand how statistical issues play out in practice.

    Buy a plant, dig a hole in the ground, drop the plant in it, and cover it up waiting for blooms to suddenly appear. If only it were that simple. The overall idea of gardening is basic, but gardening is very intricate. It

    It was pretty obvious that people found something on the internet for free and put it on Amazon to sell, but for only 99 cents I figured there wasn't much to lose so I bought one. Turned out to be totally useless. There was no table of contents and there were two or three blank pages between each recipe. That meant a lot of clicking on the Kindle just to see what's there. I didn't bother trying to click through all the recipes - I was afraid I'd wear out my little clicker. Instead, I went to google and immediately found what people were downloading, a .pdf file with 470 recipes in alphabetical order. Hence "Artichoke Chicken and Olives" was next to "Artichoke and Cheese Dip" but if you want to browse all the chicken recipes you're out of luck. So I converted this .pdf file to something I could work with and proceeded to reorganize the recipes into categories and build a table of contents. Now if you've got a chicken sitting in your fridge screaming at you to do something before it gets too old you can go to the "Chicken and Turkey" section of the table of contents and scan through the titles or click on the first one and start glancing at the recipes until you find something that strikes your fancy. I also standardized the recipe formats and abbreviations and included a little information about converting the U.S. measurements for those of you that have advanced on to the metric system and now only use teaspoons for stirring your tea. Some of these recipes mention brand name products. If those products aren't available where you are you're just going to have to call me bad names and either wing it or try another recipe. There are plenty of recipes that only call for natural and/or fresh ingredients though. Revised: 30 August 2011

    For the media, statistics are routinely 'damning', 'horrifying', or, occasionally, 'encouraging'. Yet, for all their ubiquity, most of us really don't know what to make of statistics. Exploring the history, mathematics, philosophy and practical use of statistics, Eileen Magnello - accompanied by Bill Mayblin's intelligent graphic illustration - traces the rise of statistics from the ancient Babylonians, Egyptians and Chinese, to the censuses of Romans and the Greeks, and the modern emergence of the term itself in Europe. She explores the 'vital statistics' of, in particular, William Farr, and the mathematical statistics of Karl Pearson and R.A. Fisher.She even tells how knowledge of statistics can prolong one's life, as it did for evolutionary biologist Stephen Jay Gould, given eight months to live after a cancer diagnoses in 1982 - and he lived until 2002. This title offers an enjoyable, surprise-filled tour through a subject that is both fascinating and crucial to understanding our world.

    

    This manual contains fully worked-out solutions to all of the odd-numbered exercises in the text, giving students a way to check their answers and ensure that they took the correct steps to arrive at an answer.

    Topics covered include matrix multiplication, row reduction, matrix inverse, orthogonality and computation. The self-teaching book is loaded with examples and graphics and provides a wide array of probing problems, accompanying solutions, and a glossary. Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Essentially, you make an initial guess, and then get more data to improve it. Bayes Theorem, or Bayes Rule, has a ton of real world applications, from estimating your risk of a heart attack to making recommendations on Netflix But It Isn't That Complicated This book is a short introduction to Bayes Theorem. It is only 15 pages long, and is intended to show you how Bayes Theorem works as quickly as possible. The examples are intentionally kept simple to focus solely on Bayes Theorem without requiring that the reader know complicated probability distributions. If you want to learn the basics of Bayes Theorem as quickly as possible, with some easy to duplicate examples, this is a good book for you.

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community