Industry experts Jacqueline Nolis and Emily Robinson lay out the soft skills you’ll need alongside your technical know-how in order to succeed in the field. Following their clear and simple instructions you’ll craft a resume that hiring managers will love, learn how to ace your interview, and ensure you hit the ground running in your first months at your new job. Once you’ve gotten your foot in the door, learn to thrive as a data scientist by handling high expectations, dealing with stakeholders, and managing failures. Finally, you’ll look towards the future and learn about how to join the broader data science community, leaving a job gracefully, and plotting your career path. With this book by your side you’ll have everything you need to ensure a rewarding and productive role in data science.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    And she can't concentrate on her tennis matches when she's worried about the questions she missed on the big test! Luckily for her, she befriends Ryota, a patient physics geek who uses real-world examples to help her understand classical mechanics-and improve her tennis game in the process!In The Manga Guide to Physics, you'll follow alongside Megumi as she learns about the physics of everyday objects like roller skates, slingshots, braking cars, and tennis serves. In no time, you'll master tough concepts like momentum and impulse, parabolic motion, and the relationship between force, mass, and acceleration.You'll also learn how to:Apply Newton's three laws of motion to real-life problems Determine how objects will move after a collision Draw vector diagrams and simplify complex problems using trigonometry Calculate how an object's kinetic energy changes as its potential energy increases If you're mystified by the basics of physics or you just need a refresher, The Manga Guide to Physics will get you up to speed in a lively, quirky, and practical way.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    Drawing on their hugely popular BBC Radio 4 show More or Less,, journalist Michael Blastland and internationally known economist Andrew Dilnot delight, amuse, and convert American mathphobes by showing how our everyday experiences make sense of numbers. The radical premise of The Numbers Game is to show how much we already know, and give practical ways to use our knowledge to become cannier consumers of the media. In each concise chapter, the authors take on a different theme—such as size, chance, averages, targets, risk, measurement, and data—and present it as a memorable and entertaining story. If you’ve ever wondered what “average” really means, whether the scare stories about cancer risk should convince you to change your behavior, or whether a story you read in the paper is biased (and how), you need this book. Blastland and Dilnot show how to survive and thrive on the torrent of numbers that pours through everyday life. It’s the essential guide to every cause you love or hate, and every issue you follow, in the language everyone uses.

    Each year, the series editor and guest editor curates a truly exceptional collection. The only shared traits among all these diverse styles, voices, and stories are the extraordinarily high caliber of writing, and the pure passion they tap into that can only come from sports.

    The blades start moving in 60 seconds. What do you do? If you want to work at Google, or any of America's best companies, you need to have an answer to this and other puzzling questions. Are You Smart Enough to Work at Google? guides readers through the surprising solutions to dozens of the most challenging interview questions. The book covers the importance of creative thinking, ways to get a leg up on the competition, what your Facebook page says about you, and much more. Are You Smart Enough to Work at Google? is a must-read for anyone who wants to succeed in today's job market.

    But over the past decade, a wave of dramatic findings in the cutting-edge science of endurance has completely overturned our understanding of human limitation. Endure widely disseminates these findings for the first time: It’s the brain that dictates how far we can go—which means we can always push ourselves further.Hutchinson presents an overview of science’s search for understanding human fatigue, from crude experiments with electricity and frogs’ legs to sophisticated brain imaging technology. Going beyond the traditional mechanical view of human limits (like a car with a brick on its gas pedal, we go until the tank runs out of gas), he instead argues that a key element in endurance is how the brain responds to distress signals—whether heat, or cold, or muscles screaming with lactic acid—and reveals that we can train to improve brain response.An elite distance runner himself, Hutchinson takes us to the forefront of the new sports psychology—brain electrode jolts, computer-based training, subliminal messaging—and presents startling new discoveries enhancing the performance of athletes today and shows how anyone can utilize these tactics to bolster their own performance—and get the most out of their bodies.

    The authors have extensive experience both managing data analysts and conducting their own data analyses, and have carefully observed what produces coherent results and what fails to produce useful insights into data. This book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    The Shot. The Flu Game. Michael Jordan is responsible for sublime moments so ingrained in sports history that they have their own names. When most people think of him, they think of his beautiful shots with the game on the line, his body totally in sync with the ball -- hitting nothing but net. But for all his greatness, this scion of a complex family from North Carolina's Coastal Plain has a darker side: he's a ruthless competitor and a lover of high stakes. There's never been a biography that encompassed the dual nature of his character and looked so deeply at Jordan on and off the court -- until now.Basketball journalist Roland Lazenby spent almost thirty years covering Michael Jordan's career in college and the pros. He witnessed Jordan's growth from a skinny rookie to the instantly recognizable global ambassador for basketball whose business savvy and success have millions of kids still wanting to be just like Mike. Yet Lazenby also witnessed the Michael Jordan whose drive and appetite are more fearsome and more insatiable than any of his fans could begin to know. Michael Jordan: The Life explores both sides of his personality to reveal the fullest, most compelling story of the man who is Michael Jordan.Lazenby draws on his personal relationships with Jordan's coaches; countless interviews with Jordan's friends, teammates, and family members; and interviews with Jordan himself to provide the first truly definitive study of Michael Jordan: the player, the icon, and the man.

    By spinning 28 mathematical tales, Orlin shows us that calculus is simply another language to express the very things we humans grapple with every day -- love, risk, time, and most importantly, change. Divided into two parts, "Moments" and "Eternities," and drawing on everyone from Sherlock Holmes to Mark Twain to David Foster Wallace, Change is the Only Constant unearths connections between calculus, art, literature, and a beloved dog named Elvis. This is not just math for math's sake; it's math for the sake of becoming a wiser and more thoughtful human.

    We want to be able to figure out who will win an election, if the stock market will crash, or if a suspect definitely committed a crime. But the odds are not in our favor. Life is full of uncertainty --- indeed, scientific advances indicate that the universe might be fundamentally inexact --- and humans are terrible at guessing. When asked to predict the outcome of a chance event, we are almost always wrong.Thankfully, there is hope. As award-winning mathematician Ian Stewart reveals, over the course of history, mathematics has given us some of the tools we need to better manage the uncertainty that pervades our lives. From forecasting, to medical research, to figuring out how to win Let's Make a Deal, Do Dice Play God? is a surprising and satisfying tour of what we can know, and what we never will.

    In a way, you already know them. Only you don’t – not really. In a sense, they are you. Only they’re not entirely. They inform and shape the most important decisions in your life. But you’re almost certainly unaware of their intervention. They are the Ten Types of Human. Who are they? What are they for? How did they get into your head? We want to believe that there are some things we would never do. We want to believe that there are others we always would. But how can we be sure? What are our limits? Do we have limits?The answer lies with the Ten Types of Human: the people we become when we are faced with life's most difficult decisions. But who or what are these Types? Where do they come from? How did they get into our heads?The Ten Types of Human is a pioneering examination of human nature. It looks at the best and worst that human beings are capable of, and asks why. It explores the frontiers of the human experience, excavating the forces that shape our thoughts and actions in extreme situations. It begins in a courtroom and journeys across four continents and through the lives of some exceptional people, in search of answers.Mixing cutting-edge neuroscience, social psychology and visceral true stories, The Ten Types of Human is at once a provocation and a roadmap of the hidden parts of us. It is a book to inspire; to refashion our understanding of our many selves and semblances; and ultimately to find fresh ways to be free.

    It allows one to gain information by discarding information, namely, the individuality of the observations. Stigler s second pillar, information measurement, challenges the importance of big data by noting that observations are not all equally important: the amount of information in a data set is often proportional to only the square root of the number of observations, not the absolute number. The third idea is likelihood, the calibration of inferences with the use of probability. Intercomparison is the principle that statistical comparisons do not need to be made with respect to an external standard. The fifth pillar is regression, both a paradox (tall parents on average produce shorter children; tall children on average have shorter parents) and the basis of inference, including Bayesian inference and causal reasoning. The sixth concept captures the importance of experimental design for example, by recognizing the gains to be had from a combinatorial approach with rigorous randomization. The seventh idea is the residual the notion that a complicated phenomenon can be simplified by subtracting the effect of known causes, leaving a residual phenomenon that can be explained more easily.The Seven Pillars of Statistical Wisdom presents an original, unified account of statistical science that will fascinate the interested layperson and engage the professional statistician."