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Advanced Analytics with R and Tableau
Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of RAbout This Book* Comprehensive guide that will bring out the creativity inside you in visualizing the results of complex calculations using Tableau and R* Combine Tableau analytics and visualization with the power of R using this step-by-step guide* Wondering how R can be used with Tableau? This book is your one-stop solution.Who This Book Is ForThis book will appeal to Tableau users who want to go beyond the Tableau interface and deploy the full potential of Tableau, by using R to perform advanced analytics with Tableau.A basic familiarity with R is useful but not compulsory, as the ...
Data Scientists at Work
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,...
The Decision Intelligence Handbook
Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap. They present a step-by-step method for integrating technology into decisions that bridge from actions to desired outcomes, with a focus on systems that act in an advisory, human-in-the-loop capacity to decision makers. This handbook addresses three widespread data-driven decision-making problems: How can decision makers use data and technology to ensure desired outcomes? How can technology teams communicate effectively with decision makers to maximize the return on their data and technology investments? How can organizational decision makers assess and improve their decisions over time?
Becoming a Data Head
"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, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak int...
Tableau: Creating Interactive Data Visualizations
Illustrate your data in a more interactive way by implementing data visualization principles and creating visual stories using Tableau About This Book Use data visualization principles to help you to design dashboards that enlighten and support business decisions Integrate your data to provide mashed-up dashboards Connect to various data sources and understand what data is appropriate for Tableau Public Understand chart types and when to use specific chart types with different types of data Who This Book Is For Data scientists who have just started using Tableau and want to build on the skills using practical examples. Familiarity with previous versions of Tableau will be helpful, but not ne...
SQL Server 2012 with PowerShell V3 Cookbook
SQL Server 2012 with PowerShell V3 Cookbook" is an example-focused book that provides step-by-step instructions on how to accomplish specific SQL Server tasks using PowerShell. Each recipe is followed by an analysis of the steps or design decisions taken, and additional information about the task at hand. Working scripts are provided for all examples so that you can dive in right away. You can read this book sequentially by chapter, or you can pick and choose which topics you need right away, This book is written for the SQL Server database professional (DBA, developer, BI developer) who wants to use PowerShell to automate, integrate, and simplify database tasks. A little bit of scripting background is helpful, but not necessary.
Practical Automated Machine Learning on Azure
Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply automated machine learning (AutoML), a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology. Building machine-learning models is an iterative and time-consuming process. Even those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Learn how companies in different industries are benefiting from AutoML Get started with AutoML using Azure Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning Understand how data analysts, BI professions, developers can use AutoML in their familiar tools and experiences Learn how to get started using AutoML for use cases including classification, regression, and forecasting.
Crushing the IT Gender Bias
Conscious and unconscious bias, societal pressures, and discomfort with women’s ambition are issues that women are confronted with in any male-dominated setting, and tech is no exception. Statistically, women are a disproportionately small percentage of the technology industry. How did we get here, what is changing, and what can future generations of women in STEM expect? In Crushing the IT Gender Bias, author Kellyn Pot’Vin-Gorman applies her two decades of experience in tech to these meaningful questions, plus many more. As a mentor and sponsor of women in the database and development communities, Pot’Vin-Gorman uses experience, visualizations of hard data, and industry interviews to...
Braggin Rights
Taylor Fleming is a thirty-six year old Texas rancher who covets her independence enough to keep her life simple, no strings attached. As partner to her father’s vast cattle ranch, she has enough to keep her busy without taking on a serious relationship with any of the women who clamor for her attention. When a neighboring aging rancher fills the Fleming’s life with aggravation and vandalism, Taylor is forced to confront the old man’s estranged daughter, Jen Holland. But convincing Jen to intervene becomes another task entirely. After an accident leaves Taylor with imposed bed rest, her cowgirl independence is tested to the limit. Soon Jen is facing an ultimatum. To keep her father’s property from being sold on the courthouse steps, Jen must dust off her nursing skills and take on a job she could never have anticipated—being caregiver to the stubborn Taylor Fleming…
Data Science Algorithms in a Week
Build a strong foundation of machine learning algorithms in 7 days Key FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook Description Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models ca...
