Data Scientists At Work

Author: Sebastian Gutierrez
Publisher: Apress
ISBN: 143026599X
Size: 42.39 MB
Format: PDF
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Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report. Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang, LinkedIn); venture capital (Roger Ehrenberg, IA Ventures); enterprise cloud computing and neuroscience (Eric Jonas, formerly Salesforce.com); newspaper and media (Chris Wiggins, The New York Times); streaming television (Caitlin Smallwood, Netflix); music forecast (Victor Hu, Next Big Sound); strategic intelligence (Amy Heineike, Quid); environmental big data (André Karpištšenko, Planet OS); geospatial marketing intelligence (Jonathan Lenaghan, PlaceIQ); advertising (Claudia Perlich, Dstillery); fashion e-commerce (Anna Smith, Rent the Runway); specialty retail (Erin Shellman, Nordstrom); email marketing (John Foreman, MailChimp); predictive sales intelligence (Kira Radinsky, SalesPredict); and humanitarian nonprofit (Jake Porway, DataKind). The book features a stimulating foreword by Google's Director of Research, Peter Norvig. Each of these data scientists shares how he or she tailors the torrent-taming techniques of big data, data visualization, search, and statistics to specific jobs by dint of ingenuity, imagination, patience, and passion. Data Scientists at Work parts the curtain on the interviewees’ earliest data projects, how they became data scientists, their discoveries and surprises in working with data, their thoughts on the past, present, and future of the profession, their experiences of team collaboration within their organizations, and the insights they have gained as they get their hands dirty refining mountains of raw data into objects of commercial, scientific, and educational value for their organizations and clients.

Scientists At Work

Author: Susan Ring
Publisher: Capstone
ISBN: 9780736852678
Size: 40.21 MB
Format: PDF, ePub
View: 434
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Explores different science careers, including working in a lab, working with animals, investigating space, and examining the past.

Academic Scientists At Work

Author: Jeremy Boss
Publisher: Springer Science & Business Media
ISBN: 0387354271
Size: 15.64 MB
Format: PDF, ePub, Docs
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A guide for scientists on the journey from the end of a postdoctoral career to the point of promotion to Associate Professor, this 2nd edition focuses on three aspects of the academic setting: Scholarship, Teaching, and Service. Valuable advice is provided on such topics as choosing and landing an academic job; setting up and managing the lab; obtaining funds; organizing, writing, and publishing your work; teaching and mentoring; and the promotion and tenure process.

Academic Scientists At Work

Author: Jeremy M. Boss
Publisher: Springer Science & Business Media
ISBN: 0306483815
Size: 34.86 MB
Format: PDF
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This work guides the scientist on the journey from the end of a postdoctoral career to the point of promotion to Associate Professor. It includes a CD-ROM containing template worksheets and point-by-point instructions on how to complete them, with downloadable blank worksheet versions. Included are six database program files that can be used to help the reader organize his/her laboratory specific reagents.

Big Data At Work

Author: Thomas Davenport
Publisher: Harvard Business Review Press
ISBN: 1422168166
Size: 15.34 MB
Format: PDF, Docs
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Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.

Doing Data Science

Author: Cathy O'Neil
Publisher: "O'Reilly Media, Inc."
ISBN: 144936389X
Size: 59.86 MB
Format: PDF, Kindle
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Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

The Data Science Handbook

Author: Field Cady
Publisher: John Wiley & Sons
ISBN: 1119092949
Size: 36.30 MB
Format: PDF, ePub, Mobi
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A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Python For Data Science For Dummies

Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1118843983
Size: 55.32 MB
Format: PDF
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Unleash the power of Python for your data analysis projectswith For Dummies! Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to take advantage ofPython programming to acquire, organize, process, and analyze largeamounts of information and use basic statistics concepts toidentify trends and patterns. You’ll get familiar with thePython development environment, manipulate data, design compellingvisualizations, and solve scientific computing challenges as youwork your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming andstatistics to help you build a solid foundation in data scienceconcepts like probability, random distributions, hypothesistesting, and regression models Explains objects, functions, modules, and libraries and theirrole in data analysis Walks you through some of the most widely-used libraries,including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python,Python for Data Science For Dummies is your practical guideto getting a grip on data overload and doing interesting thingswith the oodles of information you uncover.

Climate Scientists At Work

Author: Rebecca E. Hirsch
Publisher: Britannica Digital Learning
ISBN: 1625136633
Size: 27.56 MB
Format: PDF, ePub, Mobi
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Scientists around the world are working to understand our changing climate. Learn what they do and how you can help. You may want to become a citizen scientist! This title supports NGSS for Earth and Human Activity.

Scientists At Work

Author: John Noble Wilford
Publisher: Dodd Mead
ISBN:
Size: 13.84 MB
Format: PDF
View: 3704
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Selected from the New York Times series, these articles by leading science journalists cover a wide range of subjects and describe the creative aspects of the scientist conducting research in the lab and in the field