Author : Wayne B. Nelson
Publisher : SIAM
Page : 157 pages
File Size : 12,5 MB
Release : 2003-01-01
Category : Technology & Engineering
ISBN : 0898715229
Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.
Author : Rafael A. Irizarry
Publisher : CRC Press
Page : 537 pages
File Size : 16,49 MB
Release : 2016-10-04
Category : Mathematics
ISBN : 1498775861
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Author : Mert Damlapinar
Publisher : NLITX
Page : 347 pages
File Size : 41,81 MB
Release : 2019-11-11
Category : Business & Economics
ISBN :
Analytics of Life provides the reader with a broad overview of the field of data analytics and artificial intelligence. It provides the layperson an understanding of the various stages of artificial intelligence, the risks and powerful benefits. And it provides a way to look at big data and machine learning that enables us to make the most of this exciting new realm of technology in our day-to-day jobs and our small businesses. Questions you can find answers* * What is artificial intelligence (AI)? * What is the difference between AI, machine learning and data analytics? * Which jobs AI will replace, which jobs are safe from data analytics revolution? * Why data analytics is the best career move? * How can I apply data analytics in my job or small business? Who is this book for? * Managers and business professionals * Marketers, product managers, and business strategists * Entrepreneurs, founders and startups team members * Consultants, advisors and educators * Almost anybody who has an interest in the future According to an article by Cade Metz in The New York Times, "Researchers say computer systems are learning from lots and lots of digitized books and news articles that could bake old attitudes into new technology." Oxford University professor Nick Bostrom argues that if machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control. MIT professor Max Tegmark describes and illuminates the recent, ground-breaking advances in Artificial Intelligence and how it might overtake human intelligence. As Oxford University economist Daniel Susskind points out, technological progress could bring about unprecedented prosperity, solving one of humanity's oldest problems: how to make sure that everyone has enough to live on. Distinguished AI researcher and professor of computer science at UC Berkeley, Russell Stuart suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Industry experts claim that AI will have a negative impact on blue-collar jobs, but Mert predicts that Americans and Europeans will experience a strong impact on white-collar jobs as well. And Mert also provides research results and a clear description of which jobs will be affected and how soon, which jobs could be enhanced with AI. Analytics of Life also provides solutions and insight into some of the most profound changes to come in human history.
Author : Seth Stephens-Davidowitz
Publisher : HarperCollins
Page : 320 pages
File Size : 44,29 MB
Release : 2022-05-10
Category : Self-Help
ISBN : 0062880934
"Seth Stephens-Davidowitz is more than a data scientist. He is a prophet for how to use the data revolution to reimagine your life. Don’t Trust Your Gut is a tour de force—an intoxicating blend of analysis, humor, and humanity.” — Daniel H. Pink, #1 New York Times bestselling author of When, Drive, and To Sell Is Human Big decisions are hard. We consult friends and family, make sense of confusing “expert” advice online, maybe we read a self-help book to guide us. In the end, we usually just do what feels right, pursuing high stakes self-improvement—such as who we marry, how to date, where to live, what makes us happy—based solely on what our gut instinct tells us. But what if our gut is wrong? Biased, unpredictable, and misinformed, our gut, it turns out, is not all that reliable. And data can prove this. In Don’t Trust Your Gut, economist, former Google data scientist, and New York Times bestselling author Seth Stephens-Davidowitz reveals just how wrong we really are when it comes to improving our own lives. In the past decade, scholars have mined enormous datasets to find remarkable new approaches to life’s biggest self-help puzzles. Data from hundreds of thousands of dating profiles have revealed surprising successful strategies to get a date; data from hundreds of millions of tax records have uncovered the best places to raise children; data from millions of career trajectories have found previously unknown reasons why some rise to the top. Telling fascinating, unexpected stories with these numbers and the latest big data research, Stephens-Davidowitz exposes that, while we often think we know how to better ourselves, the numbers disagree. Hard facts and figures consistently contradict our instincts and demonstrate self-help that actually works—whether it involves the best time in life to start a business or how happy it actually makes us to skip a friend’s birthday party for a night of Netflix on the couch. From the boring careers that produce the most wealth, to the old-school, data-backed relationship advice so well-worn it’s become a literal joke, he unearths the startling conclusions that the right data can teach us about who we are and what will make our lives better. Lively, engrossing, and provocative, the end result opens up a new world of self-improvement made possible with massive troves of data. Packed with fresh, entertaining insights, Don’t Trust Your Gut redefines how to tackle our most consequential choices, one that hacks the market inefficiencies of life and leads us to make smarter decisions about how to improve our lives. Because in the end, the numbers don’t lie.
Author : Charles D. Morgan
Publisher : Morgan James Publishing
Page : 346 pages
File Size : 19,6 MB
Release : 2015-01-20
Category : Business & Economics
ISBN : 1630474665
Thanks to Edward Snowden and the N.S.A., “Big Data” is a hot---and controversial---topic these days. In Charles D. Morgan’s lively memoir, "Matters of Life and Data", he shows that data gathering itself is neither good nor bad---it’s how it’s used that matters. But Big Data isn’t the whole story here---Morgan is also a champion race car driver, a jet pilot, and an all-around gadget-geek-turned-business-visionary. Life is about solving the problems we’re faced with, and Charles Morgan’s life has been one of trial, error, and great achievement. His story will inspire all who read it.
Author : Giorgia Lupi
Publisher : Chronicle Books
Page : 304 pages
File Size : 37,32 MB
Release : 2016-09-13
Category : Design
ISBN : 1616895462
Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.
Author : Jer Thorp
Publisher : MCD
Page : 320 pages
File Size : 35,37 MB
Release : 2021-05-04
Category : Social Science
ISBN : 0374720517
Jer Thorp’s analysis of the word “data” in 10,325 New York Times stories written between 1984 and 2018 shows a distinct trend: among the words most closely associated with “data,” we find not only its classic companions “information” and “digital,” but also a variety of new neighbors—from “scandal” and “misinformation” to “ethics,” “friends,” and “play.” To live in data in the twenty-first century is to be incessantly extracted from, classified and categorized, statisti-fied, sold, and surveilled. Data—our data—is mined and processed for profit, power, and political gain. In Living in Data, Thorp asks a crucial question of our time: How do we stop passively inhabiting data, and instead become active citizens of it? Threading a data story through hippo attacks, glaciers, and school gymnasiums, around colossal rice piles, and over active minefields, Living in Data reminds us that the future of data is still wide open, that there are ways to transcend facts and figures and to find more visceral ways to engage with data, that there are always new stories to be told about how data can be used. Punctuated with Thorp's original and informative illustrations, Living in Data not only redefines what data is, but reimagines who gets to speak its language and how to use its power to create a more just and democratic future. Timely and inspiring, Living in Data gives us a much-needed path forward.
Author : Ron S. Kenett
Publisher : John Wiley & Sons
Page : 142 pages
File Size : 13,37 MB
Release : 2019-04-01
Category : Science
ISBN : 111957076X
The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." —Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." —Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University
Author : Jacqueline Kazil
Publisher : "O'Reilly Media, Inc."
Page : 507 pages
File Size : 31,8 MB
Release : 2016-02-04
Category : Computers
ISBN : 1491948779
How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process
Author : Mireille Hildebrandt
Publisher : Edward Elgar Publishing
Page : 296 pages
File Size : 28,31 MB
Release : 2020-01-31
Category : Law
ISBN : 1788972007
This ground-breaking and timely book explores how big data, artificial intelligence and algorithms are creating new types of agency, and the impact that this is having on our lives and the rule of law. Addressing the issues in a thoughtful, cross-disciplinary manner, leading scholars in law, philosophy, computer science and politics examine the ways in which data-driven agency is transforming democratic practices and the meaning of individual choice.
