Analytics of Life
Analytics of Life

Author: Mert Damlapinar

Publisher: NLITX

Published: 2019-11-11

Total Pages: 347

ISBN-13:

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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.

Analytics in Healthcare and the Life Sciences
Analytics in Healthcare and the Life Sciences

Author: Thomas H. Davenport

Publisher: Pearson Education

Published: 2013-11-04

Total Pages: 351

ISBN-13: 0133408701

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Make healthcare analytics work: leverage its powerful opportunities for improving outcomes, cost, and efficiency.This book gives you thepractical frameworks, strategies, tactics, and case studies you need to go beyond talk to action. The contributing healthcare analytics innovators survey the field’s current state, present start-to-finish guidance for planning and implementation, and help decision-makers prepare for tomorrow’s advances. They present in-depth case studies revealing how leading organizations have organized and executed analytic strategies that work, and fully cover the primary applications of analytics in all three sectors of the healthcare ecosystem: Provider, Payer, and Life Sciences. Co-published with the International Institute for Analytics (IIA), this book features the combined expertise of IIA’s team of leading health analytics practitioners and researchers. Each chapter is written by a member of the IIA faculty, and bridges the latest research findings with proven best practices. This book will be valuable to professionals and decision-makers throughout the healthcare ecosystem, including provider organization clinicians and managers; life sciences researchers and practitioners; and informaticists, actuaries, and managers at payer organizations. It will also be valuable in diverse analytics, operations, and IT courses in business, engineering, and healthcare certificate programs.

Data Analysis for the Life Sciences with R
Data Analysis for the Life Sciences with R

Author: Rafael A. Irizarry

Publisher: CRC Press

Published: 2016-10-04

Total Pages: 537

ISBN-13: 1498775861

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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.

The Analytics Lifecycle Toolkit
The Analytics Lifecycle Toolkit

Author: Gregory S. Nelson

Publisher: John Wiley & Sons

Published: 2018-03-07

Total Pages: 468

ISBN-13: 1119425093

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An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.

Data Analytics and AI
Data Analytics and AI

Author: Jay Liebowitz

Publisher: CRC Press

Published: 2020-08-06

Total Pages: 196

ISBN-13: 1000094677

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Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.

Analytics of Life
Analytics of Life

Author: Mert Damlapinar

Publisher:

Published: 2020-03-14

Total Pages: 348

ISBN-13: 9781098300975

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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 the 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 futureAccording 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."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.

INFORMS Analytics Body of Knowledge
INFORMS Analytics Body of Knowledge

Author: James J. Cochran

Publisher: John Wiley & Sons

Published: 2018-10-23

Total Pages: 400

ISBN-13: 1119483212

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Standardizes the definition and framework of analytics #2 on Book Authority’s list of the Best New Analytics Books to Read in 2019 (January 2019) We all want to make a difference. We all want our work to enrich the world. As analytics professionals, we are fortunate - this is our time! We live in a world of pervasive data and ubiquitous, powerful computation. This convergence has inspired and accelerated the development of both analytic techniques and tools and this potential for analytics to have an impact has been a huge call to action for organizations, universities, and governments. This title from Institute for Operations Research and the Management Sciences (INFORMS) represents the perspectives of some of the most respected experts on analytics. Readers with various backgrounds in analytics – from novices to experienced professionals – will benefit from reading about and implementing the concepts and methods covered here. Peer reviewed chapters provide readers with in-depth insights and a better understanding of the dynamic field of analytics The INFORMS Analytics Body of Knowledge documents the core concepts and skills with which an analytics professional should be familiar; establishes a dynamic resource that will be used by practitioners to increase their understanding of analytics; and, presents instructors with a framework for developing academic courses and programs in analytics.

Predictive Analytics
Predictive Analytics

Author: Eric Siegel

Publisher: John Wiley & Sons

Published: 2016-01-12

Total Pages: 368

ISBN-13: 1119153654

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"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a

Data Analysis for Business, Economics, and Policy
Data Analysis for Business, Economics, and Policy

Author: Gábor Békés

Publisher: Cambridge University Press

Published: 2021-05-06

Total Pages: 741

ISBN-13: 1108483011

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A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Lean Analytics
Lean Analytics

Author: Alistair Croll

Publisher: "O'Reilly Media, Inc."

Published: 2024-02-23

Total Pages: 403

ISBN-13: 1098168151

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Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products