Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only moderately accurate solutions. This engaging book is an antidote to the rigor mortis brought on by too much mathematical rigor, teaching us how to guess answers without needing a proof or an exact calculation.In Street-Fighting Mathematics, Sanjoy Mahajan builds, sharpens, and demonstrates tools for educated guessing and down-and-dirty, opportunistic problem solving across diverse fields of knowledge--from mathematics to management. Mahajan describes six tools: dimensional analysis, easy cases, lumping, picture proofs, successive approximation, and reasoning by analogy. Illustrating each tool with numerous examples, he carefully separates the tool--the general principle--from the particular application so that the reader can most easily grasp the tool itself to use on problems of particular interest. Street-Fighting Mathematics grew out of a short course taught by the author at MIT for students ranging from first-year undergraduates to graduate students ready for careers in physics, mathematics, management, electrical engineering, computer science, and biology. They benefited from an approach that avoided rigor and taught them how to use mathematics to solve real problems.Street-Fighting Mathematics will appear in print and online under a Creative Commons Noncommercial Share Alike license.

    This e-book is a completely new way to learn Brazilian Portuguese vocabulary fast - and for free! Start speaking Brazilian Portuguese in minutes with the powerful learning methods you will master in this book.The vocabulary words you’ll find in Learn BrazilianPortuguese - Word Power 101 were hand selected by our Brazilian Portuguese language teachers as the top 101 most frequently used words in the Brazilian Portuguese language. With each entry, you’ll see the word and a vibrant image to help remember the meaning. You’ll hear the word (separate free download) to master the pronunciation. Then you’ll see how the word is actually used in everyday speech with sample sentences and phrases. Learning Brazilian Portuguese vocabulary has never been easier!In this book, you’ll get: - 101 of the most frequently used Brazilian Portuguese vocabulary words - Audio with authentic native Brazilian Portuguese pronunciation *Supplementary mp3 audio files are a separate download - Vibrant photos and images to help memorization - Useful and practical sample sentences and phrases Purchase Learn BrazilianPortuguese - Word Power 101 today to start mastering Brazilian Portuguese vocabulary in the fastest, easiest and most fun way possible!

    The Text Was Designed To Familiarize Students With The Foundations And Principles Of Computer Science And To Strengthen The Students' Ability To Carry Out Formal And Rigorous Mathematical Arguments. In The New Fourth Edition, Author Peter Linz Has Offered A Straightforward, Uncomplicated Treatment Of Formal Languages And Automata And Avoids Excessive Mathematical Detail So That Students May Focus On And Understand The Underlying Principles. In An Effort To Further The Accessibility And Comprehension Of The Text, The Author Has Added New Illustrative Examples Throughout.

    Algorithm design techniques are also stressed and basic algorithm analysis is covered. Most of the programs are written in Pascal.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    The heart of this creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design.

    In the Mastering Emacs ebook you will learn the answers to all the concepts that take weeks, months or even years to truly learn, all in one place.“Emacs is such a hard editor to learn”But why is it so hard to learn? As it turns out, it's almost always the same handful of issues that everyone faces.If you have tried to learn Emacs you will have struggled with the same problems everyone faces, and few tutorials to see you through it.I have dedicated the first half of the book to explaining the essence of Emacs — and in doing so, how to overcome these issues:Memorizing Emacs’s keys: You will learn Emacs one key at a time, starting with the arrow keys. To feel productive in Emacs, it’s important you start on an equal footing — without too many new concepts and keys to memorize. Each chapter will introduce more keys and concepts so you can learn at your own pace. Discovering new modes and features: Emacs is a self-documenting editor, and I will teach you how to use the apropos, info, and describe system to discover new modes and features, or help you find things you forgot! Customizing Emacs: You don’t have to learn Emacs Lisp to alter a lot of Emacs’s functionality. Most changes you want to make are possible using Emacs’s Customize interface and I will show you how to use it efficiently. Understanding the terminology: Emacs is so old it predates almost every other editor and all modern user interfaces. I have an entire chapter dedicated to the unique terminology in Emacs; how it is different from other editors, and what that means to you.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.

    Jonathan Stark shows you how to leverage your existing web development skills to build native iPhone applications using these technologies." --John Allsopp, author and founder of Web Directions"Jonathan's book is the most comprehensive documentation available for developing web applications for mobile Safari. Not just great tech coverage, this book is an easy read of purely fascinating mobile tidbits in a fun colloquial style. Must have for all PhoneGap developers." -- Brian LeRoux, Nitobi SoftwareIt's a fact: if you know HTML, CSS, and JavaScript, you already have the tools you need to develop your own iPhone apps. With this book, you'll learn how to use these open source web technologies to design and build apps for the iPhone and iPod Touch on the platform of your choice-without using Objective-C or Cocoa.Device-agnostic mobile apps are the wave of the future, and this book shows you how to create one product for several platforms. You'll find guidelines for converting your product into a native iPhone app using the free PhoneGap framework. And you'll learn why releasing your product as a web app first helps you find, fix, and test bugs much faster than if you went straight to the App Store with a product built with Apple's tools.Build iPhone apps with tools you already know how to useLearn how to make an existing website look and behave like an iPhone appAdd native-looking animations to your web app using jQTouchTake advantage of client-side data storage with apps that run even when the iPhone is offlineHook into advanced iPhone features -- including the accelerometer, geolocation, and vibration -- with JavaScriptSubmit your applications to the App Store with XcodeThis book received valuable community input through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at http://labs.oreilly.com/ofps.html.

    Boundless works with subject matter experts to select the best open educational resources available on the web, review the content for quality, and create introductory, college-level textbooks designed to meet the study needs of university students.<br><br>This textbook covers:<br><br><b>Human Anatomy and Physiology Introduction</b> -- Anatomy and Physiology Overview, Life, Homeostasis, Anatomical Terms, Clinical Cases<br><br><b>General Chemistry</b> -- Matter and Energy, Element Properties: Atomic structure, Chemical Bonds, Chemical Reactions, Inorganic Compounds, Organic Compounds<br><br><b>Cellular Structure and Function</b> -- the study of cells, Cell membranes and the fluid mosaic model, Transport across membranes, How reception works in cell signaling, Nucleus and Ribosomes, Organelles, The Cytoskeleton, External cellular components, Cell division: process and importance, The cell cycle, Transcription and translation, RNA processing, Translation to a polypeptide, Transcription, Apoptosis signals an orderly cell death<br><br><b>Tissues</b> -- Epithelial Tissue, Cell Junctions, Clinical Cases, Tissue Repair, Tissue Development, Cancer, Connective Tissue, Membranes, Nervous Tissue<br><br><b>The Integumentary System</b> -- The Skin, Accessory Structures of the Skin, Functions of the Integumentary System, Wound Healing, Integumentary System Development, Skin Disorders, Imbalances, Diseases, and Clinical Cases<br><br><b>Skeletal Tissue</b> -- Cartilage, Bone Classification, Bone Formation, Bone and Calcium, Bone Development, Bone Diseases, Disorders, Imbalances, and Clinical Cases<br><br><b>The Skeletal System</b> -- Overview of the Musculoskeletal system, Divisions of the Skeletal System, The Axial Skeleton, Skull, Hyoid Bone, Vertebral Column, Thorax, Clinical Cases of the Axial Skeleton, The Appendicular Skeleton, The Pectoral (Shoulder) Girdle, Upper Limb, The Pelvic (Hip) Girdle, Lower Limb, Skeletal System Development, Clinical Cases of the Appendicular Skeleton<br><br><b>Joints</b> -- Classification of Joints, Synovial Joints, Joint Development, Clinical Cases<br><br><b>Muscle Tissue</b> -- Overview of Muscle Tissue, Skeletal Muscle, Control of Muscle Tension, Muscle Metabolism, Exercise and Skeletal Muscle Tissue, Smooth Muscle, Clinical Cases: Muscle Disorders, Development of Muscle<br><br><b>The Muscular System</b> -- Overview of the Muscular System, Head And Neck Muscles, Trunk Muscles, Muscles of the Upper Limb, Muscles of the Lower Limb, Clinical Cases and Muscular System Disorders<br><br><b>Nervous Tissue</b> -- Overview of the Nervous System, Neuroglia, Neurons, Collections of Nervous Tissue, Neurophysiology<br><br><b>Central Nervous System (CNS)</b> -- The Brain, Consciousness, Sleep, Language, and Memory, Protection of the Brain, Parts of The Brain Stem, The Cerebellum, The Diencephalon, Cerebral Cortex (or Cerebral Hemispheres), Functional Systems of the Cerebral Cortex, Development of the CNS, Brain Disorders and Clinical Cases, The Spinal Cord, Spinal Cord Anatomy, Disorders and Clinical Cases of the Spinal Cord<br><br><b>Peripheral Nervous System (PNS)</b> -- Sensation, Sensory Receptors, Somatosensory System, Nerves, Cranial Nerves, Spinal Nerves, Distribution of Spinal Nerves, Motor Activity, Motor Pathways, Reflexes, Pain, Development of the Nervous System, Disorders of Spinal Nerves and Clinical Cases<br><br><b>Autonomic Nervous System (ANS)</b> -- Autonomic Nervous System, ANS Anatomy, Physiology of ANS,

    This simple microcontroller board lets artists and designers build a variety of amazing objects and prototypes that interact with the physical world. With this cookbook you can dive right in and experiment with more than a hundred tips and techniques, no matter what your skill level is.The recipes in this book provide solutions for most common problems and questions Arduino users have, including everything from programming fundamentals to working with sensors, motors, lights, and sound, or communicating over wired and wireless networks. You'll find the examples and advice you need to begin, expand, and enhance your projects right away.Get to know the Arduino development environmentUnderstand the core elements of the Arduino programming languageUse common output devices for light, motion, and soundInteract with almost any device that has a remote controlLearn techniques for handling time delays and time measurementUse simple ways to transfer digital information from sensors to the Arduino deviceCreate complex projects that incorporate shields and external modulesUse and modify existing Arduino libraries, and learn how to create your own

    R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http: //www.imperial.ac.uk/bio/research/crawl... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

    Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.

    Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.