Federal Data Science

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making. No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective. Offers a range of data science models, engineering tools, and federal use-cases Provides foundational observations into government data resources and requirements Introduces experiences and examples of data openness from the US and other countries A step-by-step guide for the conversion of government towards data-driven policy making Focuses on presenting data models that work within the constraints of the US government Presents the why, the what, and the how of injecting AI into federal culture and software systems

Produk Detail:

  • Author : Feras A. Batarseh
  • Publisher : Academic Press
  • Pages : 256 pages
  • ISBN : 012812444X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKFederal Data Science

Federal Data Science

Federal Data Science
  • Author : Feras A. Batarseh,Ruixin Yang
  • Publisher : Academic Press
  • Release : 21 September 2017
GET THIS BOOKFederal Data Science

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits

Data Science for Business and Decision Making

Data Science for Business and Decision Making
  • Author : Luiz Paulo Fávero,Patrícia Belfiore
  • Publisher : Academic Press
  • Release : 11 April 2019
GET THIS BOOKData Science for Business and Decision Making

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and

Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications
  • Author : Philipp Kats,David Katz
  • Publisher : Packt Publishing Ltd
  • Release : 30 August 2019
GET THIS BOOKLearn Python by Building Data Science Applications

Understand the constructs of the Python programming language and use them to build data science projects Key Features Learn the basics of developing applications with Python and deploy your first data application Take your first steps in Python programming by understanding and using data structures, variables, and loops Delve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in Python Book Description Python is the most widely used programming language for building data science applications. Complete

Data Science for COVID-19 Volume 1

Data Science for COVID-19 Volume 1
  • Author : Utku Kose,Deepak Gupta,Victor Hugo Costa de Albuquerque,Ashish Khanna
  • Publisher : Academic Press
  • Release : 27 May 2021
GET THIS BOOKData Science for COVID-19 Volume 1

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative

Data Democracy

Data Democracy
  • Author : Feras A. Batarseh,Ruixin Yang
  • Publisher : Academic Press
  • Release : 28 January 2020
GET THIS BOOKData Democracy

This book provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it.

Data Science in the Public Interest: Improving Government Performance in the Workforce

Data Science in the Public Interest: Improving Government Performance in the Workforce
  • Author : Joshua D. Hawley
  • Publisher : W.E. Upjohn Institute
  • Release : 22 July 2020
GET THIS BOOKData Science in the Public Interest: Improving Government Performance in the Workforce

This book is about how new and underutilized types of big data sources can inform public policy decisions related to workforce development. Hawley describes how government is currently using data to inform decisions about the workforce at the state and local levels. He then moves beyond standardized performance metrics designed to serve federal agency requirements and discusses how government can improve data gathering and analysis to provide better, up-to-date information for government decision making.

Applied Data Science

Applied Data Science
  • Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
  • Publisher : Springer
  • Release : 13 June 2019
GET THIS BOOKApplied Data Science

This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and

Big Data and Analytics Applications in Government

Big Data and Analytics Applications in Government
  • Author : Gregory Richards
  • Publisher : Auerbach Publications
  • Release : 17 October 2021
GET THIS BOOKBig Data and Analytics Applications in Government

Public Sector organizations represent an important aspect of the economy of most countries, ranging from 30-40% of GDP. The application of Big Data and Analytics (BDA) techniques can greatly enhance the efficiency of these organizations, but it is early days yet for public managers who might not really understand what BDA is and how to apply it. This book represents a global repository of case studies along with academic and practitioner viewpoints on the application of BDA in public sector

Game Theory for Data Science

Game Theory for Data Science
  • Author : Boi Faltings,Goran Radanovic
  • Publisher : Morgan & Claypool Publishers
  • Release : 19 September 2017
GET THIS BOOKGame Theory for Data Science

Intelligent systems often depend on data provided by information agents, for example, sensor data or crowdsourced human computation. Providing accurate and relevant data requires costly effort that agents may not always be willing to provide. Thus, it becomes important not only to verify the correctness of data, but also to provide incentives so that agents that provide high-quality data are rewarded while those that do not are discouraged by low rewards. We cover different settings and the assumptions they admit,

Data Democracy

Data Democracy
  • Author : Feras A. Batarseh,Ruixin Yang
  • Publisher : Academic Press
  • Release : 21 January 2020
GET THIS BOOKData Democracy

Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not

Data Science for Librarians

Data Science for Librarians
  • Author : Yunfei Du,Hammad Rauf Khan
  • Publisher : ABC-CLIO
  • Release : 26 March 2020
GET THIS BOOKData Science for Librarians

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how

Data Science Applications Using Python and R

Data Science Applications Using Python and R
  • Author : Jeffrey Strickland
  • Publisher : Unknown Publisher
  • Release : 23 August 2020
GET THIS BOOKData Science Applications Using Python and R

Data Science Applications using Python and R is the second book in a series that began in 2018. This volume is dedicated to text analytics and natural language processing. Using real data, the author leads the reader through the analysis of Tweet sentiment analysis, banking product-group complaint analysis, presidential debate analysis, and more. The book covers text mining, natural language processing (NLP), vectorizing text data, discrete classifiers, bag-of-words (BOW) models, sentiment analysis, and Latent Dirichlet Allocation (LDA). The book offers complete

Introduction to Biomedical Data Science

Introduction to Biomedical Data Science
  • Author : Robert Hoyt,Robert Muenchen
  • Publisher : Lulu.com
  • Release : 25 November 2019
GET THIS BOOKIntroduction to Biomedical Data Science

Introduction to Biomedical Data Science aims to fill the data science knowledge gap experienced by many clinical, administrative and technical staff. The textbook begins with an overview of what biomedical data science is and then embarks on a tour of topics beginning with spreadsheet tips and tricks and ending with artificial intelligence. In between, important topics are covered such as biostatistics, data visualization, database systems, big data, programming languages, bioinformatics, and machine learning. The textbook is available as a paperback

Predictive Analytics

Predictive Analytics
  • Author : Dursun Delen
  • Publisher : FT Press Analytics
  • Release : 30 October 2020
GET THIS BOOKPredictive Analytics

In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web

OECD Digital Government Studies The Path to Becoming a Data-Driven Public Sector

OECD Digital Government Studies The Path to Becoming a Data-Driven Public Sector
  • Author : OECD
  • Publisher : OECD Publishing
  • Release : 28 November 2019
GET THIS BOOKOECD Digital Government Studies The Path to Becoming a Data-Driven Public Sector

This report highlights the important role data can play in creating conditions that improve public services, increase the effectiveness of public spending and inform ethical and privacy considerations. It presents a data-driven public sector framework that can help countries or organisations assess the elements needed for using data to make better-informed decisions across public sectors.