The Go Programming Language
The Go Programming Language is the authoritative resource for any programmer who wants to learn Go. It shows how to write clear and idiomatic Go to solve real-world problems. The book does not assume prior knowledge of Go nor experience with any specific language, so you'll find it accessible whether you're most comfortable with JavaScript, Ruby, Python, Java, or C++. The first chapter is a tutorial on the basic concepts of Go, introduced through programs for file I/O and text processing, simple graphics, and web clients and servers. Early chapters cover the structural elements of Go programs: syntax, control flow, data types, and the organization of a program into packages, files, and functions. The examples illustrate many packages from the standard library and show how to create new ones of your own. Later chapters explain the package mechanism in more detail, and how to build, test, and maintain projects using the go tool. The chapters on methods and interfaces introduce G ...
The Go Programming Language is the authoritative resource for any programmer who wants to learn Go. It shows how to write clear and idiomatic Go to solve real-world problems. The book does not assume prior knowledge of Go nor experience with any specific language, so you'll find it accessible whether you're most comfortable with JavaScript, Ruby, Python, Java, or C++. The first chapter is a tutorial on the basic concepts of Go, introduced through programs for file I/O and text processing, simple graphics, and web clients and servers. Early chapters cover the structural elements of Go programs: syntax, control flow, data types, and the organization of a program into packages, files, and functions. The examples illustrate many packages from the standard library and show how to create new ones of your own. Later chapters explain the package mechanism in more detail, and how to build, test, and maintain projects using the go tool. The chapters on methods and interfaces introduce G ...
Panel Data Analysis using EViews
A comprehensive and accessible guide to panel data analysis using EViews software. This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. ...
A comprehensive and accessible guide to panel data analysis using EViews software. This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. ...
Learning Informatica PowerCenter 9.x
Informatica PowerCenter provides the perfect platform to utilize and leverage business data. It allows you to easily, conveniently, and efficiently work on different types of data. This book covers functionality such as creating/importing source and target, identifying errors, and debugging your mapping through a series of comprehensive tutorials. Besides learning about types of Slowly Changing Dimensions (SCDs), you will learn to create and link workflows. As you progress, exhaustive knowledge of transformations and techniques to create folders, migrate code, and optimize system performance will be explored in detail. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter. ...
Informatica PowerCenter provides the perfect platform to utilize and leverage business data. It allows you to easily, conveniently, and efficiently work on different types of data. This book covers functionality such as creating/importing source and target, identifying errors, and debugging your mapping through a series of comprehensive tutorials. Besides learning about types of Slowly Changing Dimensions (SCDs), you will learn to create and link workflows. As you progress, exhaustive knowledge of transformations and techniques to create folders, migrate code, and optimize system performance will be explored in detail. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter. ...
VMware vRealize Operations Performance and Capacity Management
VMware vRealize Operations is a suite of products that automates operations management using patented analytics and an integrated approach to performance, capacity, and configuration management. vRealize Operations Manager is the most important component of this suite that helps administrators to maintain and troubleshoot their VMware environment as well as their physical environment. This book takes you through the fundamental differences between a Software-Defined Data Center and a classic physical data center, and how these differences impact both architecture and operations. From a strategic point of view, you will come across the most common challenges associated with performance management in a Software-Defined Data Center. Furthermore, you will learn all the key counters in vSphere and vRealize Operations, understand their dependencies, and acquaint yourself with practical solutions to configure them for a healthy virtual environment. ...
VMware vRealize Operations is a suite of products that automates operations management using patented analytics and an integrated approach to performance, capacity, and configuration management. vRealize Operations Manager is the most important component of this suite that helps administrators to maintain and troubleshoot their VMware environment as well as their physical environment. This book takes you through the fundamental differences between a Software-Defined Data Center and a classic physical data center, and how these differences impact both architecture and operations. From a strategic point of view, you will come across the most common challenges associated with performance management in a Software-Defined Data Center. Furthermore, you will learn all the key counters in vSphere and vRealize Operations, understand their dependencies, and acquaint yourself with practical solutions to configure them for a healthy virtual environment. ...
Social Media Mining with R
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. However, analyzing this ever-growing pile of data is quite tricky and, if done erroneously, could lead to wrong inferences. By using this essential guide, you will gain hands-on experience with generating insights from social media data. This book provides detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to help you accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. ...
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. However, analyzing this ever-growing pile of data is quite tricky and, if done erroneously, could lead to wrong inferences. By using this essential guide, you will gain hands-on experience with generating insights from social media data. This book provides detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to help you accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. ...
Fast Data Processing with Spark
Spark is a framework for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and inbuilt tools for interactive query analysis (Shark), large-scale graph processing and analysis (Bagel), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big data sets. Fast Data Processing with Spark covers how to write distributed map reduce style programs with Spark. The book will guide you through every step required to write effective distributed programs from setting up your cluster and interactively exploring the API, to deploying your job to the cluster, and tuning it for your purposes. ...
Spark is a framework for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and inbuilt tools for interactive query analysis (Shark), large-scale graph processing and analysis (Bagel), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big data sets. Fast Data Processing with Spark covers how to write distributed map reduce style programs with Spark. The book will guide you through every step required to write effective distributed programs from setting up your cluster and interactively exploring the API, to deploying your job to the cluster, and tuning it for your purposes. ...
Learning SciPy for Numerical and Scientific Computing
It's essential to incorporate workflow data and code from various sources in order to create fast and effective algorithms to solve complex problems in science and engineering. Data is coming at us faster, dirtier, and at an ever increasing rate. There is no need to employ difficult-to-maintain code, or expensive mathematical engines to solve your numerical computations anymore. SciPy guarantees fast, accurate, and easy-to-code solutions to your numerical and scientific computing applications. Learning SciPy for Numerical and Scientific Computing unveils secrets to some of the most critical mathematical and scientific computing problems and will play an instrumental role in supporting your research. The book will teach you how to quickly and efficiently use different modules and routines from the SciPy library to cover the vast scope of numerical mathematics with its simplistic practical approach that's easy to follow. ...
It's essential to incorporate workflow data and code from various sources in order to create fast and effective algorithms to solve complex problems in science and engineering. Data is coming at us faster, dirtier, and at an ever increasing rate. There is no need to employ difficult-to-maintain code, or expensive mathematical engines to solve your numerical computations anymore. SciPy guarantees fast, accurate, and easy-to-code solutions to your numerical and scientific computing applications. Learning SciPy for Numerical and Scientific Computing unveils secrets to some of the most critical mathematical and scientific computing problems and will play an instrumental role in supporting your research. The book will teach you how to quickly and efficiently use different modules and routines from the SciPy library to cover the vast scope of numerical mathematics with its simplistic practical approach that's easy to follow. ...
Graphing Data with R
It's much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You'll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance. Anyone who wants to analyze data will find something useful here - even if you don't have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start. ...
It's much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You'll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance. Anyone who wants to analyze data will find something useful here - even if you don't have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start. ...
Mastering Apache Spark
Apache Spark is an in-memory cluster based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and SQL. It operates at unprecedented speeds, is easy to use and offers a rich set of data transformations. This book aims to take your limited knowledge of Spark to the next level by teaching you how to expand Spark functionality. The book commences with an overview of the Spark eco-system. You will learn how to use MLlib to create a fully working neural net for handwriting recognition. You will then discover how stream processing can be tuned for optimal performance and to ensure parallel processing. The book extends to show how to incorporate H20 for machine learning, Titan for graph based storage, Databricks for cloud-based Spark. Intermediate Scala based code examples are provided for Apache Spark module processing in a CentOS Linux and Databricks cloud environment. ...
Apache Spark is an in-memory cluster based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and SQL. It operates at unprecedented speeds, is easy to use and offers a rich set of data transformations. This book aims to take your limited knowledge of Spark to the next level by teaching you how to expand Spark functionality. The book commences with an overview of the Spark eco-system. You will learn how to use MLlib to create a fully working neural net for handwriting recognition. You will then discover how stream processing can be tuned for optimal performance and to ensure parallel processing. The book extends to show how to incorporate H20 for machine learning, Titan for graph based storage, Databricks for cloud-based Spark. Intermediate Scala based code examples are provided for Apache Spark module processing in a CentOS Linux and Databricks cloud environment. ...
Algorithms, 4th Edition
The latest version of Sedgewick's best-selling series, reflecting an indispensable body of knowledge developed over the past several decades. Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books. ...
The latest version of Sedgewick's best-selling series, reflecting an indispensable body of knowledge developed over the past several decades. Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. New Java implementations written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. Algorithms are studied in the context of important scientific, engineering, and commercial applications. Clients and algorithms are expressed in real code, not the pseudo-code found in many other books. ...