Fast Data Processing with Spark, 2nd Edition
Spark is a framework used 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 built-in tools for interactive query analysis (Spark SQL), large-scale graph processing and analysis (GraphX), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big datasets. Fast Data Processing with Spark - Second Edition covers how to write distributed 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 developing analytics applications and tuning them for your purposes. ...
Spark is a framework used 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 built-in tools for interactive query analysis (Spark SQL), large-scale graph processing and analysis (GraphX), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big datasets. Fast Data Processing with Spark - Second Edition covers how to write distributed 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 developing analytics applications and tuning them for your purposes. ...
File Management Made Simple, Windows Edition
Managing data is an essential skill that every PC user should have. Surprisingly though, a large number of users--even highly experienced users--exhibit poor file management skills, resulting in frustration and lost data. File Management Made Simple can resolve this by providing you with the skills and best practices needed for creating, managing and protecting your data. Do any of the following scenarios sound familiar to you? You've downloaded an attachment from your e-mail, but aren't sure where you downloaded it to. You spent an entire evening working on a document only to discover the next morning that you didn't save it to your flash drive like you thought you had? Unfortunately, for a vast number of PC users, scenarios like these are all too common. These situations are not only extremely frustrating for the user, but also tend to discourage them from ever wanting to touch a PC again! However, these problems and others can be easily rectified with this brief, book, by your si ...
Managing data is an essential skill that every PC user should have. Surprisingly though, a large number of users--even highly experienced users--exhibit poor file management skills, resulting in frustration and lost data. File Management Made Simple can resolve this by providing you with the skills and best practices needed for creating, managing and protecting your data. Do any of the following scenarios sound familiar to you? You've downloaded an attachment from your e-mail, but aren't sure where you downloaded it to. You spent an entire evening working on a document only to discover the next morning that you didn't save it to your flash drive like you thought you had? Unfortunately, for a vast number of PC users, scenarios like these are all too common. These situations are not only extremely frustrating for the user, but also tend to discourage them from ever wanting to touch a PC again! However, these problems and others can be easily rectified with this brief, book, by your si ...
Learning Flask Framework
Flask is a small and powerful web development framework for Python. It does not presume or force a developer to use a particular tool or library. Flask supports extensions that can add application features as if they were implemented in Flask itself. Flask's main task is to build web applications quickly and with less code. With its lightweight and efficient web development framework, Flask combines rapid development and clean, simple design. This book will take you through the basics of learning how to apply your knowledge of Python to the web. Starting with the creation of a “Hello world” Flask app, you will be introduced to the most common Flask APIs and Flask's interactive debugger. You will learn how to store and retrieve blog posts from a relational database using an ORM and also to map URLs to views. Furthermore, you will walk through template blocks, inheritance, file uploads, and static assets. ...
Flask is a small and powerful web development framework for Python. It does not presume or force a developer to use a particular tool or library. Flask supports extensions that can add application features as if they were implemented in Flask itself. Flask's main task is to build web applications quickly and with less code. With its lightweight and efficient web development framework, Flask combines rapid development and clean, simple design. This book will take you through the basics of learning how to apply your knowledge of Python to the web. Starting with the creation of a “Hello world” Flask app, you will be introduced to the most common Flask APIs and Flask's interactive debugger. You will learn how to store and retrieve blog posts from a relational database using an ORM and also to map URLs to views. Furthermore, you will walk through template blocks, inheritance, file uploads, and static assets. ...
Learning Haskell Data Analysis
Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of code that will be used to solve a problem for that chapter. The book starts with creating databases out of existing datasets, cleaning that data, and interacting with databases within Haskell in order to produce charts for publications. It then moves towards more theoretical concepts that are fundamental to introductory data analysis, but in a context of a real-world problem with real-world data. As you progress in the book, you will be relying on code from previous chapters in order to help create new solutions quickly. By the end of the book, you will be able to manipulate, find, and analyze large and small sets of data using your own Haskell libraries. ...
Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of code that will be used to solve a problem for that chapter. The book starts with creating databases out of existing datasets, cleaning that data, and interacting with databases within Haskell in order to produce charts for publications. It then moves towards more theoretical concepts that are fundamental to introductory data analysis, but in a context of a real-world problem with real-world data. As you progress in the book, you will be relying on code from previous chapters in order to help create new solutions quickly. By the end of the book, you will be able to manipulate, find, and analyze large and small sets of data using your own Haskell libraries. ...
Practical Python AI Projects
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models, and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations. Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study. Build basic Python-based artificial intelligence (AI) applications; Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suite; Create several types of projects using Python ...
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models, and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations. Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study. Build basic Python-based artificial intelligence (AI) applications; Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suite; Create several types of projects using Python ...
Ruby Data Processing
Gain the basics of Ruby's map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex programs in 10 lines of Ruby code, an astonishingly small number. You will walk through problems and solutions which are effective because they use map, reduce, and select. As you read Ruby Data Processing, type in the code, run the code, and ponder the results. Tweak the code to test the code and see how the results change. After reading this book, you will have a deeper understanding of how to break data-processing problems into processing stages, each of which is understandable, debuggable, and composable, and how to combine the stages to solve your data-processing problem. As a result, your Ruby coding will become more efficient and your programs will be more elegant and robust. Discover Ruby data processing and how to do it using the map, reduce, and select functions; Develop compl ...
Gain the basics of Ruby's map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex programs in 10 lines of Ruby code, an astonishingly small number. You will walk through problems and solutions which are effective because they use map, reduce, and select. As you read Ruby Data Processing, type in the code, run the code, and ponder the results. Tweak the code to test the code and see how the results change. After reading this book, you will have a deeper understanding of how to break data-processing problems into processing stages, each of which is understandable, debuggable, and composable, and how to combine the stages to solve your data-processing problem. As a result, your Ruby coding will become more efficient and your programs will be more elegant and robust. Discover Ruby data processing and how to do it using the map, reduce, and select functions; Develop compl ...
Learning Predictive Analytics with R
R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. ...
R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. ...
Machine Learning with R Cookbook
The 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. ...
The 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 Julia
Julia is a well-constructed programming language with fast execution speed, eliminating the classic problem of performing analysis in one language and translating it for performance into a second. This book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges. This book starts off with a refresher on installing and running Julia on different platforms. Next, you will compare the different ways of working with Julia and explore Julia's key features in-depth by looking at design and build. You will see how data works using simple statistics and analytics, and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks and observe how Julia can cooperate with external processes in order to enhance graphics and data visualization. Finally, you will look into meta-programming and learn how it adds great power to the language and establish networking and distributed computing with ...
Julia is a well-constructed programming language with fast execution speed, eliminating the classic problem of performing analysis in one language and translating it for performance into a second. This book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges. This book starts off with a refresher on installing and running Julia on different platforms. Next, you will compare the different ways of working with Julia and explore Julia's key features in-depth by looking at design and build. You will see how data works using simple statistics and analytics, and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks and observe how Julia can cooperate with external processes in order to enhance graphics and data visualization. Finally, you will look into meta-programming and learn how it adds great power to the language and establish networking and distributed computing with ...
Mastering Scientific Computing with R
With this book, you will learn not just about R, but how to use R to answer conceptual, scientific, and experimental questions. Beginning with an overview of fundamental R concepts, you'll learn how R can be used to achieve the most commonly needed scientific data analysis tasks: testing for statistically significant differences between groups and model relationships in data. You will delve into linear algebra and matrix operations with an emphasis not on the R syntax, but on how these operations can be used to address common computational or analytical needs. This book also covers the application of matrix operations for the purpose of finding structure in high-dimensional data using the principal component, exploratory factor, and confirmatory factor analysis in addition to structural equation modeling. You will also master methods for simulation and learn about an advanced analytical method. ...
With this book, you will learn not just about R, but how to use R to answer conceptual, scientific, and experimental questions. Beginning with an overview of fundamental R concepts, you'll learn how R can be used to achieve the most commonly needed scientific data analysis tasks: testing for statistically significant differences between groups and model relationships in data. You will delve into linear algebra and matrix operations with an emphasis not on the R syntax, but on how these operations can be used to address common computational or analytical needs. This book also covers the application of matrix operations for the purpose of finding structure in high-dimensional data using the principal component, exploratory factor, and confirmatory factor analysis in addition to structural equation modeling. You will also master methods for simulation and learn about an advanced analytical method. ...