Big Data Bootcamp
Investors and technology gurus have called big data one of the most important trends to come along in decades. Big Data Bootcamp explains what big data is and how you can use it in your company to become one of tomorrow's market leaders. Along the way, it explains the very latest technologies, companies, and advancements. Big data holds the keys to delivering better customer service, offering more attractive products, and unlocking innovation. That's why, to remain competitive, every organization should become a big data company. It's also why every manager and technology professional should become knowledgeable about big data and how it is transforming not just their own industries but the global economy. ...
Investors and technology gurus have called big data one of the most important trends to come along in decades. Big Data Bootcamp explains what big data is and how you can use it in your company to become one of tomorrow's market leaders. Along the way, it explains the very latest technologies, companies, and advancements. Big data holds the keys to delivering better customer service, offering more attractive products, and unlocking innovation. That's why, to remain competitive, every organization should become a big data company. It's also why every manager and technology professional should become knowledgeable about big data and how it is transforming not just their own industries but the global economy. ...
Python Data Analysis
Dive deeper into data analysis with the flexibility of Python and learn how its extensive range of scientific and mathematical libraries can be used to solve some of the toughest challenges in data analysis. Build your confidence and expertise and develop valuable skills in high demand in a world driven by Big Data with this expert data analysis book. This data science tutorial will help you learn how to effectively retrieve, clean, manipulate, and visualize data and establish a successful data analysis workflow. Apply the impressive functionality of Python's data mining tools and scientific and numerical libraries to a range of the most important tasks within data analysis and data science, and develop strategies and ideas to take control your own data analysis projects. Get to grips with statistical analysis using NumPy and SciPy, visualize data with Matplotlib, and uncover sophisticated insights through predictive analytics and machine learning with SciKit-Learn. You will also le ...
Dive deeper into data analysis with the flexibility of Python and learn how its extensive range of scientific and mathematical libraries can be used to solve some of the toughest challenges in data analysis. Build your confidence and expertise and develop valuable skills in high demand in a world driven by Big Data with this expert data analysis book. This data science tutorial will help you learn how to effectively retrieve, clean, manipulate, and visualize data and establish a successful data analysis workflow. Apply the impressive functionality of Python's data mining tools and scientific and numerical libraries to a range of the most important tasks within data analysis and data science, and develop strategies and ideas to take control your own data analysis projects. Get to grips with statistical analysis using NumPy and SciPy, visualize data with Matplotlib, and uncover sophisticated insights through predictive analytics and machine learning with SciKit-Learn. You will also le ...
Learning Core Data for iOS
This is the first Core Data book to fully reflect Apple's latest platform innovations, including its dramatic recent improvements to iCloud support. Hands-on from start to finish, it teaches you step-by-step as you create a modern data-driven iOS app using Storyboards, ARC, iOS 7, and Xcode 5. Tim Roadley introduces new patterns and best practices designed to overcome the frustrations of Core Data development. One step at a time, you'll build and extend your skills--even mastering advanced techniques such as complex model migration, deep copy, background processing, and integration with Dropbox, StackMob, and iCloud. Downloadable versions of this book's main project are provided with each chapter, so you can see exactly what your app project should look like - and get cookbook-style code for your own projects. Chapter exercises help you explore even further, whether you're a self-learner or a student in an iOS development course. ...
This is the first Core Data book to fully reflect Apple's latest platform innovations, including its dramatic recent improvements to iCloud support. Hands-on from start to finish, it teaches you step-by-step as you create a modern data-driven iOS app using Storyboards, ARC, iOS 7, and Xcode 5. Tim Roadley introduces new patterns and best practices designed to overcome the frustrations of Core Data development. One step at a time, you'll build and extend your skills--even mastering advanced techniques such as complex model migration, deep copy, background processing, and integration with Dropbox, StackMob, and iCloud. Downloadable versions of this book's main project are provided with each chapter, so you can see exactly what your app project should look like - and get cookbook-style code for your own projects. Chapter exercises help you explore even further, whether you're a self-learner or a student in an iOS development course. ...
Python Data Visualization Cookbook, 2nd Edition
Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how ...
Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how ...
Data Analysis with R
Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it's easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “me ...
Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it's easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “me ...
Scala Data Analysis Cookbook
This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming dat ...
This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming dat ...
Creating Data Stories with Tableau Public
Tableau Public is a very useful tool in anyone's data reporting toolbox that allows authors to add an interactive data element to any article. It allows investigative journalists and bloggers to tell a “data story”, allowing others to explore your data visualization. The relative ease of Tableau Public visualization creation allows data stories to be developed rapidly. It allows readers to explore data associations in multiple-sourced public data, and uses state-of-the-art dashboard and chart graphics to immerse the users in an interactive experience. This book offers investigative journalists, bloggers, and other data story tellers a rich discussion of visualization creation topics, features, and functions. This book allows data story tellers to quickly gain confidence in understanding and expanding their visualization-creation knowledge, and allows them to quickly create interesting, interactive data visualizations to bring a richness and vibrancy to complex articles. The b ...
Tableau Public is a very useful tool in anyone's data reporting toolbox that allows authors to add an interactive data element to any article. It allows investigative journalists and bloggers to tell a “data story”, allowing others to explore your data visualization. The relative ease of Tableau Public visualization creation allows data stories to be developed rapidly. It allows readers to explore data associations in multiple-sourced public data, and uses state-of-the-art dashboard and chart graphics to immerse the users in an interactive experience. This book offers investigative journalists, bloggers, and other data story tellers a rich discussion of visualization creation topics, features, and functions. This book allows data story tellers to quickly gain confidence in understanding and expanding their visualization-creation knowledge, and allows them to quickly create interesting, interactive data visualizations to bring a richness and vibrancy to complex articles. The b ...
Big Data Analytics with Spark
This book is a step-by-step guide for learning how to use Spark for different types of big-data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, MLlib, and Spark ML. Big Data Analytics with Spark shows you how to use Spark and leverage its easy-to-use features to increase your productivity. You learn to perform fast data analysis using its in-memory caching and advanced execution engine, employ in-memory computing capabilities for building high-performance machine learning and low-latency interactive analytics applications, and much more. Moreover, the book shows you how to use Spark as a single integrated platform for a variety of data processing tasks, including ETL pipelines, BI, live data stream processing, graph analytics, and machine learning. The book also includes a chapter on Scala, the hottest functional programming l ...
This book is a step-by-step guide for learning how to use Spark for different types of big-data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, MLlib, and Spark ML. Big Data Analytics with Spark shows you how to use Spark and leverage its easy-to-use features to increase your productivity. You learn to perform fast data analysis using its in-memory caching and advanced execution engine, employ in-memory computing capabilities for building high-performance machine learning and low-latency interactive analytics applications, and much more. Moreover, the book shows you how to use Spark as a single integrated platform for a variety of data processing tasks, including ETL pipelines, BI, live data stream processing, graph analytics, and machine learning. The book also includes a chapter on Scala, the hottest functional programming l ...
Scalable Big Data Architecture
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it's often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed dat ...
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it's often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed dat ...
Big Data Analytics with R and Hadoop
Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing. Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop. ...
Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing. Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop. ...