Author:
Publisher:
ISBN:
Category : Armed Forces
Languages : en
Pages : 464
Book Description
Signal
Author:
Publisher:
ISBN:
Category : Armed Forces
Languages : en
Pages : 464
Book Description
Publisher:
ISBN:
Category : Armed Forces
Languages : en
Pages : 464
Book Description
DFAS Telecommunications
Author: United States. General Accounting Office
Publisher:
ISBN:
Category : Communications, Military
Languages : en
Pages : 24
Book Description
Publisher:
ISBN:
Category : Communications, Military
Languages : en
Pages : 24
Book Description
FEDERAL INTERAGENCY DATA-SHARING AND NATIONAL SECURITY... HEARING... COMMITTEE ON GOVERNMENT REFORM, HOUSE OF REPRESENTATIVES... 107TH CONGR
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
Book Description
Federal Interagency Data-sharing and National Security
Author: United States. Congress. House. Committee on Government Reform. Subcommittee on National Security, Veterans Affairs, and International Relations
Publisher:
ISBN:
Category : Political Science
Languages : en
Pages : 88
Book Description
Publisher:
ISBN:
Category : Political Science
Languages : en
Pages : 88
Book Description
Military Bases
Author: United States. General Accounting Office
Publisher:
ISBN:
Category : Military bases
Languages : en
Pages : 120
Book Description
Publisher:
ISBN:
Category : Military bases
Languages : en
Pages : 120
Book Description
R: Data Analysis and Visualization
Author: Tony Fischetti
Publisher: Packt Publishing Ltd
ISBN: 1786460483
Category : Computers
Languages : en
Pages : 1783
Book Description
Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions. Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on. Style and approach Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language.
Publisher: Packt Publishing Ltd
ISBN: 1786460483
Category : Computers
Languages : en
Pages : 1783
Book Description
Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions. Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on. Style and approach Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language.
Defense IRM poor implementation of management controls has put migration strategy at risk : report to the ranking minority member, Committee on Governmental Affairs, U.S. Senate
Author:
Publisher: DIANE Publishing
ISBN: 1428977783
Category :
Languages : en
Pages : 96
Book Description
Publisher: DIANE Publishing
ISBN: 1428977783
Category :
Languages : en
Pages : 96
Book Description
Defense management tools for measuring and managing Defense agency performance could be strengthened : report to the Committee on Armed Services, U.S. Senate.
Author:
Publisher: DIANE Publishing
ISBN: 1428935339
Category :
Languages : en
Pages : 60
Book Description
Publisher: DIANE Publishing
ISBN: 1428935339
Category :
Languages : en
Pages : 60
Book Description
Defense IRM
Author: United States. General Accounting Office
Publisher:
ISBN:
Category : Information resources management
Languages : en
Pages : 96
Book Description
Publisher:
ISBN:
Category : Information resources management
Languages : en
Pages : 96
Book Description
Challenge and Consequence-- Forcing Change to ECommerce
Author: Ralph W. Notto
Publisher: Wheatmark, Inc.
ISBN: 158736414X
Category : Business & Economics
Languages : en
Pages : 414
Book Description
Notto traces the history of electronic commerce and the consequent changes in the flow and use of information in the last quarter of the 20th century. He emphasizes electronic data interchange (EDI) as an essential component in the evolution of electronic commerce. Having worked on this volume from 1987 to 2002, Notto, a systems engineer, writes as
Publisher: Wheatmark, Inc.
ISBN: 158736414X
Category : Business & Economics
Languages : en
Pages : 414
Book Description
Notto traces the history of electronic commerce and the consequent changes in the flow and use of information in the last quarter of the 20th century. He emphasizes electronic data interchange (EDI) as an essential component in the evolution of electronic commerce. Having worked on this volume from 1987 to 2002, Notto, a systems engineer, writes as