This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Whether you are a student struggling to fulfill a math or science requirement, or you are embarking on a career change that requires a new skill set, A Mind for Numbers offers the tools you need to get a better grasp of that intimidating material. Engineering professor Barbara Oakley knows firsthand how it feels to struggle with math. She flunked her way through high school math and science courses, before enlisting in the army immediately after graduation. When she saw how her lack of mathematical and technical savvy severely limited her options—both to rise in the military and to explore other careers—she returned to school with a newfound determination to re-tool her brain to master the very subjects that had given her so much trouble throughout her entire life.
In A Mind for Numbers, Dr. Oakley lets us in on the secrets to learning effectively—secrets that even dedicated and successful students wish they’d known earlier. Contrary to popular belief, math requires creative, as well as analytical, thinking. Most people think that there’s only one way to do a problem, when in actuality, there are often a number of different solutions—you just need the creativity to see them. For example, there are more than three hundred different known proofs of the Pythagorean Theorem. In short, studying a problem in a laser-focused way until you reach a solution is not an effective way to learn. Rather, it involves taking the time to step away from a problem and allow the more relaxed and creative part of the brain to take over. The learning strategies in this book apply not only to math and science, but to any subject in which we struggle. We all have what it takes to excel in areas that don't seem to come naturally to us at first, and learning them does not have to be as painful as we might think!
From the Trade Paperback edition.
The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.
Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?
How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.
Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Ideal for beginners, this book shows you how to work with modules and other hardware in the popular Fez Spider Starter Kit, and teaches you how to program your gadgets with Visual Studio C# Express and the .NET Micro Framework 4.1 SDK. You’ll soon learn a wide range of programming techniques along with the skills to design your own projects.Get to know the software and hardware with a simple LED projectDownload code from the companion site to build and test each projectBuild a spy camera that automatically captures and saves images at regular intervalsConstruct a simple animated game with the joystick moduleCreate a web server that sends messages you draw or write on the touchscreen moduleBuild a gadget that backs up digital images from an SD card to a USB flash driveLearn about other .NET Gadgeteer modules for creating environmental sensors, an MP3 player, and a WiFi network
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
--Hans Camenzind, inventor of the 555 timer (the world's most successful integrated circuit), and author of Much Ado About Almost Nothing: Man's Encounter with the Electron (Booklocker.com)
"A fabulous book: well written, well paced, fun, and informative. I also love the sense of humor. It's very good at disarming the fear. And it's gorgeous. I'll be recommending this book highly."
--Tom Igoe, author of Physical Computing and Making Things Talk
Want to learn the fundamentals of electronics in a fun, hands-on way? With Make: Electronics, you'll start working on real projects as soon as you crack open the book. Explore all of the key components and essential principles through a series of fascinating experiments. You'll build the circuits first, then learn the theory behind them!
Build working devices, from simple to complex You'll start with the basics and then move on to more complicated projects. Go from switching circuits to integrated circuits, and from simple alarms to programmable microcontrollers. Step-by-step instructions and more than 500 full-color photographs and illustrations will help you use -- and understand -- electronics concepts and techniques.Discover by breaking things: experiment with components and learn from failure Set up a tricked-out project space: make a work area at home, equipped with the tools and parts you'll need Learn about key electronic components and their functions within a circuit Create an intrusion alarm, holiday lights, wearable electronic jewelry, audio processors, a reflex tester, and a combination lock Build an autonomous robot cart that can sense its environment and avoid obstacles Get clear, easy-to-understand explanations of what you're doing and why
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
See Additional Notes at the back of the book for instructions to download the accompanying interactive App which brings the 250+ topics to life by allowing you to insert your own values. Visually on a phone or tablet it looks almost identical to the eBook pages, except you can edit the inputs to update the graphics and calculations to reflect those changes.
There is also a comprehensive PC version to download with even more features both applications can be unlocked with your eBook purchase receipt for no additional charge.
Education Bundle: eBook + PC software + App at a tiny fraction of the previously published price.
Achieving Accuracy‘s missile descriptions and discussions begin for weapon systems existing well before WW2 and cover virtually all US smart bombs, cruise and ballistic missiles of that century. Missile guidance systems have ranged from the V-1’s dead reckoning through simple, but jammable radio-controlled, to exceedingly complex self-contained inertial guidance systems discussed at length. The reader may be surprised to learn that a “smart-bomb” flew in 1917, with several different models used in anger in WW2. The Minuteman III leg of the present Triad is described in detail along with a somewhat bizarre set of proposed basing plans for the Peacekeeper Missile that were precursors of the recently proposed “Subway” basing plan for MMIII. Missile legacy includes a sub-section, necessarily less complete, describing Soviet/Russian missilery through 2000, noting that the early Soviet ballistic missile development was based almost entirely on the German V-2.
Who needs an electrical engineering degree? This intuitive guide shows how to wire, disassemble, tweak, and re-purpose everyday devices quickly and easily. Packed with full-color illustrations, photos, and diagrams, Hacking Electronics teaches by doing--each topic features fun, easy-to-follow projects. Discover how to hack sensors, accelerometers, remote controllers, ultrasonic rangefinders, motors, stereo equipment, microphones, and FM transmitters. The final chapter contains useful information on getting the most out of cheap or free bench and software tools.Safely solder, join wires, and connect switches Identify components and read schematic diagrams Understand the how and why of electronics theory Work with transistors, LEDs, and laser diode modules Power your devices with a/c supplies, batteries, or solar panels Get up and running on Arduino boards and pre-made modules Use sensors to detect everything from noxious gas to acceleration Build and modify audio amps, microphones, and transmitters Fix gadgets and scavenge useful parts from dead equipment
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Knowledge flow provides sensible and complete book of Digital Electronics, bringing together information on basic theory, functioning aspects and possible applications. With exertion problems, examples, and reconsider questions for every chapter, digital electronics comprise information on number systems, logic gates and families, binary codes and Boolean algebra, an in profundity look at multiplexers, digital arithmetic, de-multiplexers, devices for arithmetic operations, flip-flops and related devices, counters and registers, profundity look at multiplexers and data conversion circuits.
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R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.
Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done
Perfect for teachers, hobbyists, engineers, and students of all ages, this reference puts reliable, fact-checked information right at your fingertips--whether you're refreshing your memory or exploring a component for the first time. Beginners will quickly grasp important concepts, and more experienced users will find the specific details their projects require.
Volume 3 covers components for sensing the physical world, including light, sound, heat, motion, ambient, and electrical sensors.Unique: the first and only encyclopedia set on electronic components, distilled into three separate volumesIncredibly detailed: includes information distilled from hundreds of sourcesEasy to browse: parts are clearly organized by component typeAuthoritative: fact-checked by expert advisors to ensure that the information is both current and accurateReliable: a more consistent source of information than online sources, product datasheets, and manufacturer's tutorialsInstructive: each component description provides details about substitutions, common problems, and workaroundsComprehensive: Volume 1 covers power, electromagnetism, and discrete semi-conductors; Volume 2 includes integrated circuits, and light and sound sources; Volume 3 covers a range of sensing devices.
Assuming no knowledge of programming, this book guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering problems. The book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. In-depth coverage is given to input/output, a topic fundamental to many engineering applications.Winner of a 2017 Textbook Excellence Award (Texty) from the Textbook and Academic Authors AssociationPresents programming concepts and MATLAB built-in functions side-by-sideOffers a systematic, step-by-step approach, building on concepts throughout the book and facilitating easier learningIncludes sections on common pitfalls and programming guidelines to direct students toward best practicesCombines basic programming concepts, built-in functions, and advanced topics for problem solving with MATLAB to make this book uniquely suitable for a wide range of courses teaching or using MATLAB across the curriculum
This book will help you:Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification
Corresponding data sets are available at www.wiley.com/go/9781118876138.
Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Chances are you already use Excel to perform some fairly routine calculations. Now the Excel Scientific and Engineering Cookbook shows you how to leverage Excel to perform more complex calculations, too, calculations that once fell in the domain of specialized tools. It does so by putting a smorgasbord of data analysis techniques right at your fingertips. The book shows how to perform these useful tasks and others:Use Excel and VBA in generalImport data from a variety of sourcesAnalyze dataPerform calculationsVisualize the results for interpretation and presentationUse Excel to solve specific science and engineering problems
Wherever possible, the Excel Scientific and Engineering Cookbook draws on real-world examples from a range of scientific disciplines such as biology, chemistry, and physics. This way, you'll be better prepared to solve the problems you face in your everyday scientific or engineering tasks.
High on practicality and low on theory, this quick, look-up reference provides instant solutions, or "recipes," to problems both basic and advanced. And like other books in O'Reilly's popular Cookbook format, each recipe also includes a discussion on how and why it works. As a result, you can take comfort in knowing that complete, practical answers are a mere page-flip away.
You don’t need to have mastered Arduino or programming to get started. Updated for the Arduino 1.0 release, the recipes in this second edition include practical examples and guidance to help you begin, expand, and enhance your projects right away—whether you’re an artist, designer, hobbyist, student, or engineer.Get up to speed on the Arduino board and essential software concepts quicklyLearn basic techniques for reading digital and analog signalsUse Arduino with a variety of popular input devices and sensorsDrive visual displays, generate sound, and control several types of motorsInteract with devices that use remote controls, including TVs and appliancesLearn techniques for handling time delays and time measurementApply advanced coding and memory handling techniques
The network has become the core organizational structure for postmodern politics, culture, and life, replacing the modern era’s hierarchical systems. From peer-to-peer file sharing and massive multiplayer online games to contagion vectors of digital or biological viruses and global affiliations of terrorist organizations, the network form has become so invasive that nearly every aspect of contemporary society can be located within it.
Borrowing their title from the hacker term for a program that takes advantage of a flaw in a network system, Alexander R. Galloway and Eugene Thacker challenge the widespread assumption that networks are inherently egalitarian. Instead, they contend that there exist new modes of control entirely native to networks, modes that are at once highly centralized and dispersed, corporate and subversive.
In this provocative book-length essay, Galloway and Thacker argue that a whole new topology must be invented to resist and reshape the network form, one that is as asymmetrical in relationship to networks as the network is in relation to hierarchy.
Alexander R. Galloway is associate professor of culture and communications at New York University and the author of Gaming: Essays on Algorithmic Culture (Minnesota, 2006) and Protocol: How Control Exists after Decentralization.
Eugene Thacker is associate professor of new media at the Georgia Institute of Technology and the author of Biomedia (Minnesota, 2004) and The Global Genome: Biotechnology, Politics, and Culture.
For easy reading, a comprehensive list of hundreds of topics each with a graphic image and explanatory text act as a useful exam revision reminder or reference tool for professionals.
The accompanying software which brings all these images to life can be downloaded at no extra charge thereby providing an additional computer based interactive learning resource as an easy and enjoyable way to study.
A combined eBook and software package at a tiny fraction of the previously published price.
Unlock accompanying software with your eBook receipt!
The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.
Make a robot that obeys your every command—or runs on its own.
Maybe you’re a teacher who wants to show students how to build devices that can move, sense, respond, and interact with the physical world. Or perhaps you’re a hobbyist looking for a robot companion to make your world a little more futuristic. With Make an Arduino Controlled Robot, you’ll learn how to build and customize smart robots on wheels.
You will:Explore robotics concepts like movement, obstacle detection, sensors, and remote control Use Arduino to build two- and four-wheeled robots Put your robot in motion with motor shields, servos, and DC motors Work with distance sensors, infrared reflectance sensors, and remote control receivers Understand how to program your robot to take on all kinds of real-world physical challenges
Now published as a portable, learning, reference and subject revision guide students now have their own low-cost version as an eBook.
The Electronics PC software to accompany your eBook provides you with an easy and enjoyable way to study your chosen subject.
See Additional Notes for instructions to download the highly interactive PC software comprising hundreds of menu selected colorful topics where the graphic images (from your eBook) are brought to life for every value change along with many additional learning software features.
Full color printed is available for student handouts (using your values and selections) or images and text pasted to make student assignments.
Various editors are included to enable your own calculations to be explored and evaluated from simple algebraic equations to complex formula.
A combined eBook and educational software package at a tiny fraction of the previously published price.
Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.Become familiar with Python's fundamentals, including ways to develop simple applicationsLearn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database accessDiscover generalized patterns that cover a large proportion of how Python code is used in bioinformaticsLearn how to apply the principles and techniques of object-oriented programmingBenefit from the "tips and traps" section in each chapter
addresses tasks that nearly every SAS programmer needs to do - that is, make
sure that data errors are located and corrected. This book develops and
demonstrates data cleaning programs and macros that you can use as written or
modify for your own special data cleaning needs.
This book is an in-depth guide to the use of pandas for data analysis, for either the seasoned data analysis practitioner or the novice user. It provides a basic introduction to the pandas framework, and takes users through the installation of the library and the IPython interactive environment. Thereafter, you will learn basic as well as advanced features, such as MultiIndexing, modifying data structures, and sampling data, which provide powerful capabilities for data analysis.
"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business
Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management
The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark
"Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++.
Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.
In this pathbreaking book, Jeffrey Rosen explores the legal, technological, and cultural changes that have undermined our ability to control how much personal information about ourselves is communicated to others, and he proposes ways of reconstructing some of the zones of privacy that law and technology have been allowed to invade. In the eighteenth century, when the Bill of Rights was drafted, the spectacle of state agents breaking into a citizen's home and rummaging through his or her private diaries was considered the paradigm case of an unconstitutional search and seizure. But during the impeachment of President Bill Clinton, prosecutors were able to subpoena Monica Lewinsky's bookstore receipts and to retrieve unsent love letters from her home computer. And the sense of violation that Monica Lewinsky experienced is not unique. In a world in which everything that Americans read, write, and buy can be recorded and monitored in cyberspace, there is a growing danger that intimate personal information originally disclosed only to our friends and colleagues may be exposed to--and misinterpreted by--a less understanding audience of strangers.
Privacy is important, Rosen argues, because it protects us from being judged out of context in a world of short attention spans, a world in which isolated bits of intimate information can be confused with genuine knowledge. Rosen also examines the expansion of sexual-harassment law that has given employers an incentive to monitor our e-mail, Internet browsing habits, and office romances. And he suggests that some forms of offensive speech in the workplace--including the indignities allegedly suffered by Paula Jones and Anita Hill--are better conceived of as invasions of privacy than as examples of sex discrimination. Combining discussions of current events--from Kenneth Starr's tapes to DoubleClick's on-line profiles--with inno-vative legal and cultural analysis, The Unwanted Gaze offers a powerful challenge to Americans to be proactive in the face of new threats to privacy in the twenty-first century.
From the Hardcover edition.
This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.
The book utilizes Albert Einstein’s famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.
Our world is about to change.
In Digital Destiny: How the New Age of Data Will Change the Way We Live, Work, and Communicate, Shawn DuBravac, chief economist and senior director of research at the Consumer Electronics Association (CEA), argues that the groundswell of digital ownership unfolding in our lives signals the beginning of a new era for humanity. Beyond just hardware acquisition, the next decade will be defined by an all-digital lifestyle and the “Internet of Everything”—where everything, from the dishwasher to the wristwatch, is not only online, but acquiring, analyzing, and utilizing the data that surrounds us. But what does this mean in practice?
It means that some of mankind’s most pressing problems, such as hunger, disease, and security, will finally have a solution. It means that the rise of driverless cars could save thousands of American lives each year, and perhaps hundreds of thousands more around the planet. It means a departure from millennia-old practices, such as the need for urban centers. It means that massive inefficiencies, such as the supply chains in Africa allowing food to rot before it can be fed to the hungry, can be overcome. It means that individuals will have more freedom in action, work, health, and pursuits than ever before.
• B.Sc. (Computer Science)
• B.Sc. (Electronics)
• B.Sc. (Information Technology)
• B.Sc. (Physics)
• Bachelor of Computer Applications (BCA)
• Postgraduate Diploma in Computer Applications
• Master of Computer Applications (MCA)
The book emphasizes the must know concepts that should be covered in an introductory course and provides an abundance of clearly explained examples, so essential for a thorough understanding of the principles involved in the analysis and design of digital computers. The book takes students step-by-step through digital theory, focusing on:
» Number representation systems and codes for representing information in digital systems
» Use of logic gates in building digital circuits
» Basic postulates and theorems of Boolean algebra
» Karnaugh map method for simplifying Boolean functions
» Arithmetic circuits such as adders and subtractors
» Combinational circuit building blocks such as multiplexers, decoders and encoders
» Sequential circuit building blocks such as flip-flops, counters and registers
» Operation of memory elements such as RAM, DRAM, magnetic disk, magnetic bubble, optical disk, etc.
1. Number Systems and Codes
2. Logic Gates and Circuits
3. Boolean Algebra
4. Combinational Logic Circuits
5. Sequential Logic Circuits
6. Counters and Shift Registers
7. MEMORY ELEMENTS
In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.
Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and Hadoop
Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.
This book picks up where Make: Electronics left off: you'll work with components like comparators, light sensors, higher-level logic chips, multiplexers, shift registers, encoders, decoders, and magnetic sensors. You'll also learn about topics like audio amplification, randomicity, as well as positive and negative feedback. With step-by-step instructions, and hundreds of color photographs and illustrations, this book will help you use -- and understand -- intermediate to advanced electronics concepts and techniques.