Machine Learning with R CookbookThe R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics.
This book covers the basics of R by setting up a user-friendly programming environment and performing data ETL in R. Data exploration examples are provided that demonstrate how powerful data visualization and machine learning is in discovering hidden relationships. You will then dive into important machine learning topics, including data classification, regression, clustering, association rule mining, and dimension reduction. ...
Mastering matplotlibmatplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process.
You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor.
Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots.
Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering. ...
Mastering Social Media Mining with RWith an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data.
This book will teach you how powerful business cases are solved by applying machine learning techniques on social media data. You will learn about important and recent developments in the field of social media, along with a few advanced topics such as Open Authorization (OAuth). Through practical examples, you will access data from R using APIs of various social media sites such as Twitter, ...
Real Time Analytics with SAP HANASAP HANA is an in-memory database created by SAP. SAP HANA breaks traditional database barriers to simplify IT landscapes, eliminating data preparation, pre-aggregation, and tuning. SAP HANA and in-memory computing allow you to instantly access huge volumes of structured and unstructured data, including text data, from different sources.
Starting with data modeling, this fast-paced guide shows you how to add a system to SAP HANA Studio, create a schema, packages, and delivery unit. Moving on, you'll get an understanding of real-time replication via SLT and learn how to use SAP HANA Studio to perform this. We'll also have a quick look at SAP Business Object DATA service and SAP Direct Extractor for Data Load. After that, you will learn to create HANA artifacts - Analytical Privileges and Calculation View. At the end of the book, we will explore the SMART DATA access option and AFL library, and finally deliver pre-packaged functionality that can be used to build information models fas ...
Practical Data ScienceLearn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.
The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.
Become fluent in the essential concepts and terminology of data science and data engineering; Build and use a technology stack that meets industry criteria; Master the methods for retrieving actionable business knowledge; Coordinate the handling of polyglot data types in a data lake for repeatable results. ...
Modern Big Data Processing with HadoopThe complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.
This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster.
By the end of this book, you will have al ...
Data FluencyAnalytical data is a powerful tool for growing companies, but what good is it if it hides in the shadows? Bring your data to the forefront with effective visualization and communication approaches, and let Data Fluency: Empowering Your Organization with Effective Communication show you the best tools and strategies for getting the job done right. Learn the best practices of data presentation and the ways that reporting and dashboards can help organizations effectively gauge performance, identify areas for improvement, and communicate results.
Topics covered in the book include data reporting and communication, audience and user needs, data presentation tools, layout and styling, and common design failures. Those responsible for analytics, reporting, or BI implementation will find a refreshing take on data and visualization in this resource, as will report, data visualization, and dashboard designers. ...
Principles of Communications, 7th EditionZiemer and Tranter provide a thorough treatment of the principles of communications at the physical layer suitable for college seniors, beginning graduate students, and practicing engineers. This is accomplished by providing overviews of the necessary background in signal, system, probability, and random process theory required for the analog and digital communications topics covered in the book. In addition to stressing fundamental concepts, the seventh edition features sections on important areas such as spread spectrum, cellular communications, and orthogonal frequency-division multiplexing. While the book is aimed at a two-semester course, more than enough material is provided for structuring courses according to students need and instructor preference. ...
Exam Ref 70-778 Analyzing and Visualizing Data by Using Microsoft Power BIPrepare for Microsoft Exam 70-778 - and help demonstrate your real-world mastery of Power BI data analysis and visualization. Designed for experienced BI professionals and data analysts ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level.
Focus on the expertise measured by these objectives: Consume and transform data by using Power BI Desktop; Model and visualize data; Configure dashboards, reports, and apps in the Power BI Service.
This Microsoft Exam Ref: Organizes its coverage by exam objectives; Features strategic, what-if scenarios to challenge you; Assumes you have experience consuming and transforming data, modeling and visualizing data, and configuring dashboards using Excel and Power BI. ...
Exam Ref 70-779 Analyzing and Visualizing Data with Microsoft ExcelPrepare for Microsoft Exam 70-779 - and help demonstrate your real-world mastery of Microsoft Excel data analysis and visualization. Designed for BI professionals, data analysts, and others who analyze business data with Excel, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level.
Focus on the expertise measured by these objectives: Consume and transform data by using Microsoft Excel; Model data, from building and optimizing data models through creating performance KPIs, actual and target calculations, and hierarchies; Visualize data, including creating and managing PivotTables and PivotCharts, and interacting with PowerBI.
This Microsoft Exam Ref: Organizes its coverage by exam objectives; Features strategic, what-if scenarios to challenge you; Assumes you have a strong understanding of how to use Microsoft Excel to perform data analysis. ...