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"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful."
Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage
You've heard the hype around data—now get the facts.
In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning,
...Author
Pub. Date
[2023]
Language
English
Description
"This introductory book on data science builds upon an individual's innate knowledge and arms you with the tools to use this interdisciplinary academic field in everyday scenarios. With straightforward real-world examples and applications, it takes you on a path that may seem daunting but is made simple through Professor Raju's easy manner. It endows you with a holistic and flawless understanding of the fundamental principles required to build a solid...
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"The world is awash in bullshit, and we're drowning in it. Politicians are unconstrained by facts. Science is conducted by press release. Startup culture elevates bullshit to high art. These days, calling bullshit is a noble act. Based on Carl Bergstrom and Jevin West's popular course at the University of Washington, Calling Bullshit is a modern handbook to the art of skepticism. Bergstrom, a computational biologist, and West, an information scientist,...
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English
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"Covers how to secure and authenticate datasets and safely communicate with sources; Python programming basics for data science investigations; security concepts, like disk encryption; how to work with data in EML, MBOX, JSON, CSV, and SQL formats; and tricks for using the command-line interface to explore datasets packed with secrets"--
Author
Series
Pub. Date
[2024]
Language
English
Description
"Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner's guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge...
7) Data-ism: the revolution transforming decision making, consumer behavior, and almost everything else
Author
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English
Description
A technology reporter for the "New York Times" traces the rise of Big Data and explains how individuals and institutions will need to exploit, protect, and manage their data to stay competitive in the coming years.
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Monetize your company's data and data science expertise without spending a fortune on hiring independent strategy consultants to help. What if there was one simple, clear process for ensuring that all your company's data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that's most prime for achieving profitability while also moving your company closer...
Author
Pub. Date
[2020]
Language
English
Description
Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data--fake data generated from real data--so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue. Data scientists will learn how synthetic data...
Author
Pub. Date
[2019]
Language
English
Description
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the...
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English
Formats
Description
Data is fundamental to the modern world. From economic development to health care to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias, in time, money, and often with their lives. The author...
Author
Pub. Date
[2022]
Language
English
Description
"This book includes step-by-step examples and case studies that teach users the many power tricks for analyzing data in Excel. These are tips honed by Bill Jelen, "MrExcel," and Oz do Soleil during their careers run as a financial analyst charged with taking mainframe data and turning it into useful information quickly. Topics include data quality, validation, perfectly sorting with one click every time, matching lists of data, data consolidation,...
Author
Pub. Date
2021
Language
English
Description
"Data analysts are in demand everywhere today! And now, Murachѫs Python for Data Analysis shows you how to do data analysis the way the pros do. Youѫll master descriptive analysis, using Pandas to analyze the data and Seaborn to create the visualizations that let you present your findings effectively. Youѫll get started with predictive analysis, using Scikit-learn with linear regression models. And youѫll be guided right from the start by 4 real-world...
Author
Pub. Date
[2020]
Language
English
Description
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala,...
Author
Language
English
Description
"A brilliant, revelatory account of the Cold War origins of the data-mad, algorithmic twenty-first century, from the author of the acclaimed international bestseller, These Truths. The Simulmatics Corporation, founded in 1959, mined data, targeted voters, accelerated news, manipulated consumers, destabilized politics, and disordered knowledge--decades before Facebook, Google, Amazon, and Cambridge Analytica. Silicon Valley likes to imagine it has...
Author
Series
Pub. Date
[2020]
Language
English
Description
"A compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time"--
Author
Pub. Date
2022.
Language
English
Description
"A lesson in reading between the lines of the U.S. census to uncover the stories behind the data."--
"The census isn't just a data-collection process; it's a ritual, and a tool, of American democracy. Behind every neat grid of numbers is a collage of messy, human stories--you just have to know how to read them. In Democracy's Data, the data historian Dan Bouk examines the 1940 U.S. census, uncovering what those numbers both condense and cleverly...
Author
Pub. Date
[2022]
Language
English
Description
"THE EYE TEST is a necessary course correction, a call for a more balanced, personal approach to problem solving. Award-winning journalist Chris Jones makes the case for the human element-for what smart, practiced, devoted people can bring to situations that have proved resistant to analytics. Jones shares what he's learned from an army of extraordinary talents, including some of the best doctors, executives, athletes, meteorologists, magicians, designers,...
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