97 Things About Ethics Everyone In Data Science Should Know

Author : Bill Franks
Publisher : O'Reilly Media
Page : 347 pages
File Size : 55,8 Mb
Release : 2020-08-06
Category : Computers
ISBN : 9781492072638

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97 Things About Ethics Everyone in Data Science Should Know by Bill Franks Pdf

Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Concept—Tim Wilson How to Approach Ethical Transparency—Rado Kotorov Unbiased ≠ Fair—Doug Hague Rules and Rationality—Christof Wolf Brenner The Truth About AI Bias—Cassie Kozyrkov Cautionary Ethics Tales—Sherrill Hayes Fairness in the Age of Algorithms—Anna Jacobson The Ethical Data Storyteller—Brent Dykes Introducing Ethicize™, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’Neill Be Careful with "Decisions of the Heart"—Hugh Watson Understanding Passive Versus Proactive Ethics—Bill Schmarzo

Author : Bill Franks
Publisher : "O'Reilly Media, Inc."
Page : 316 pages
File Size : 42,5 Mb
Release : 2020-08-06
Category : Computers
ISBN : 9781492072614

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97 Things About Ethics Everyone in Data Science Should Know by Bill Franks Pdf

Most of the high-profile cases of real or perceived unethical activity in data science arenâ??t matters of bad intent. Rather, they occur because the ethics simply arenâ??t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Conceptâ??Tim Wilson How to Approach Ethical Transparencyâ??Rado Kotorov Unbiased ≠ Fairâ??Doug Hague Rules and Rationalityâ??Christof Wolf Brenner The Truth About AI Biasâ??Cassie Kozyrkov Cautionary Ethics Talesâ??Sherrill Hayes Fairness in the Age of Algorithmsâ??Anna Jacobson The Ethical Data Storytellerâ??Brent Dykes Introducing Ethicizeâ?¢, the Fully AI-Driven Cloud-Based Ethics Solution!â??Brian Oâ??Neill Be Careful with "Decisions of the Heart"â??Hugh Watson Understanding Passive Versus Proactive Ethicsâ??Bill Schmarzo

Author : Bill Franks
Publisher : O'Reilly Media
Page : 250 pages
File Size : 45,7 Mb
Release : 2020-08-31
Category : Computers
ISBN : 1492072664

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97 Things about Ethics Everyone in Data Should Know by Bill Franks Pdf

With this in-depth book, data professionals, managers, and tech leaders will learn powerful, real-world best practices and get a better understanding for data ethics. Contributors from top companies in technology, finance, and other industries share their experiences and lessons learned on bias, privacy, security, and data governance--the things you need to know for ethically collecting, managing, and using data.

Author : Tobias Macey
Publisher : "O'Reilly Media, Inc."
Page : 243 pages
File Size : 51,7 Mb
Release : 2021-06-11
Category : Computers
ISBN : 9781492062363

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97 Things Every Data Engineer Should Know by Tobias Macey Pdf

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

Author : David Martens
Publisher : Oxford University Press
Page : 273 pages
File Size : 54,6 Mb
Release : 2022-03-24
Category : MATHEMATICS
ISBN : 9780192847263

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Data Science Ethics by David Martens Pdf

Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - Data Science Ethics addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.

Author : Mike Loukides,Hilary Mason,DJ Patil
Publisher : "O'Reilly Media, Inc."
Page : 37 pages
File Size : 49,9 Mb
Release : 2018-07-25
Category : Computers
ISBN : 9781492078210

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Ethics and Data Science by Mike Loukides,Hilary Mason,DJ Patil Pdf

As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

Author : Bill Franks
Publisher : John Wiley & Sons
Page : 42 pages
File Size : 51,7 Mb
Release : 2012-03-19
Category : Business & Economics
ISBN : 9781118241172

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Taming The Big Data Tidal Wave by Bill Franks Pdf

You receive an e-mail. It contains an offer for a complete personal computer system. It seems like the retailer read your mind since you were exploring computers on their web site just a few hours prior.... As you drive to the store to buy the computer bundle, you get an offer for a discounted coffee from the coffee shop you are getting ready to drive past. It says that since you’re in the area, you can get 10% off if you stop by in the next 20 minutes.... As you drink your coffee, you receive an apology from the manufacturer of a product that you complained about yesterday on your Facebook page, as well as on the company’s web site.... Finally, once you get back home, you receive notice of a special armor upgrade available for purchase in your favorite online video game. It is just what is needed to get past some spots you’ve been struggling with.... Sound crazy? Are these things that can only happen in the distant future? No. All of these scenarios are possible today! Big data. Advanced analytics. Big data analytics. It seems you can’t escape such terms today. Everywhere you turn people are discussing, writing about, and promoting big data and advanced analytics. Well, you can now add this book to the discussion. What is real and what is hype? Such attention can lead one to the suspicion that perhaps the analysis of big data is something that is more hype than substance. While there has been a lot of hype over the past few years, the reality is that we are in a transformative era in terms of analytic capabilities and the leveraging of massive amounts of data. If you take the time to cut through the sometimes-over-zealous hype present in the media, you’ll find something very real and very powerful underneath it. With big data, the hype is driven by genuine excitement and anticipation of the business and consumer benefits that analyzing it will yield over time. Big data is the next wave of new data sources that will drive the next wave of analytic innovation in business, government, and academia. These innovations have the potential to radically change how organizations view their business. The analysis that big data enables will lead to decisions that are more informed and, in some cases, different from what they are today. It will yield insights that many can only dream about today. As you’ll see, there are many consistencies with the requirements to tame big data and what has always been needed to tame new data sources. However, the additional scale of big data necessitates utilizing the newest tools, technologies, methods, and processes. The old way of approaching analysis just won’t work. It is time to evolve the world of advanced analytics to the next level. That’s what this book is about. Taming the Big Data Tidal Wave isn’t just the title of this book, but rather an activity that will determine which businesses win and which lose in the next decade. By preparing and taking the initiative, organizations can ride the big data tidal wave to success rather than being pummeled underneath the crushing surf. What do you need to know and how do you prepare in order to start taming big data and generating exciting new analytics from it? Sit back, get comfortable, and prepare to find out!

Author : Mike Loukides,Hilary Mason,D. J. Patil
Publisher : Unknown
Page : 0 pages
File Size : 51,6 Mb
Release : 2018
Category : Electronic
ISBN : 9352138457

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Ethics and Data Science by Mike Loukides,Hilary Mason,D. J. Patil Pdf

Author : Mike Loukides,Hilary Mason,DJ Patil
Publisher : O'Reilly Media
Page : 40 pages
File Size : 51,8 Mb
Release : 2018-07-25
Category : Computers
ISBN : 9781492078227

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Ethics and Data Science by Mike Loukides,Hilary Mason,DJ Patil Pdf

As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

Author : James Gearheart
Publisher : SAS Institute
Page : 246 pages
File Size : 42,9 Mb
Release : 2020-06-26
Category : Computers
ISBN : 9781642958065

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End-to-End Data Science with SAS by James Gearheart Pdf

Learn data science concepts with real-world examples in SAS! End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-by-step. Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level by mastering SAS programming for machine learning models.

Author : Peter C. Bruce,Grant Fleming
Publisher : John Wiley & Sons
Page : 304 pages
File Size : 43,5 Mb
Release : 2021-04-13
Category : Computers
ISBN : 9781119741770

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Responsible Data Science by Peter C. Bruce,Grant Fleming Pdf

Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.

Author : Steven S. Skiena
Publisher : Springer
Page : 445 pages
File Size : 46,8 Mb
Release : 2017-07-01
Category : Computers
ISBN : 9783319554440

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The Data Science Design Manual by Steven S. Skiena Pdf

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

Author : Aristotle
Publisher : ReadHowYouWant.com
Page : 430 pages
File Size : 41,9 Mb
Release : 2006
Category : Philosophy
ISBN : 9781425000868

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Nicomachean Ethics by Aristotle Pdf

Aristotle's "Nicomachean Ethics" is considered to be one of the most important treatises on ethics ever written. In an incredibly detailed study of virtue and vice in man, Aristotle examines one of the most central themes to man, the nature of goodness itself. In Aristotle's "Nicomachean Ethics," he asserts that virtue is essential to happiness and that man must live in accordance with the "doctrine of the mean" (the balance between excess and deficiency) to achieve such happiness.

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 48,7 Mb
Release : 2013-07-27
Category : Computers
ISBN : 9781449374280

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Data Science for Business by Foster Provost,Tom Fawcett Pdf

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Author : Wang, John
Publisher : IGI Global
Page : 3296 pages
File Size : 54,8 Mb
Release : 2023-01-20
Category : Computers
ISBN : 9781799892212

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Encyclopedia of Data Science and Machine Learning by Wang, John Pdf

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.