Mac eBooks
Switching to the Mac: The Missing Manual, Yosemite Edition
What makes Windows refugees decide to get a Mac? Enthusiastic friends? The Apple Stores? Great-looking laptops? A "halo effect" from the popularity of iPhones and iPads? The absence of viruses and spyware? The freedom to run Windows on a Mac? In any case, there's never been a better time to switch to OS X—and there's never been a better, more authoritative book to help you do it. ...
What makes Windows refugees decide to get a Mac? Enthusiastic friends? The Apple Stores? Great-looking laptops? A "halo effect" from the popularity of iPhones and iPads? The absence of viruses and spyware? The freedom to run Windows on a Mac? In any case, there's never been a better time to switch to OS X—and there's never been a better, more authoritative book to help you do it. ...
Machine Learning with Spark
Apache Spark is a framework for distributed computing that is designed from the ground up to be optimized for low latency tasks and in-memory data storage. It is one of the few frameworks for parallel computing that combines speed, scalability, in-memory processing, and fault tolerance with ease of programming and a flexible, expressive, and powerful API design. This book guides you through the basics of Spark's API used to load and process data and prepare the data to use as input to the various machine learning models. There are detailed examples and real-world use cases for you to explore common machine learning models including recommender systems, classification, regression, clustering, and dimensionality reduction. You will cover advanced topics such as working with large-scale text data, and methods for online machine learning and model evaluation using Spark Streaming. ...
Apache Spark is a framework for distributed computing that is designed from the ground up to be optimized for low latency tasks and in-memory data storage. It is one of the few frameworks for parallel computing that combines speed, scalability, in-memory processing, and fault tolerance with ease of programming and a flexible, expressive, and powerful API design. This book guides you through the basics of Spark's API used to load and process data and prepare the data to use as input to the various machine learning models. There are detailed examples and real-world use cases for you to explore common machine learning models including recommender systems, classification, regression, clustering, and dimensionality reduction. You will cover advanced topics such as working with large-scale text data, and methods for online machine learning and model evaluation using Spark Streaming. ...
Splunk Essentials
Splunk is a powerful tool that is used extensively to search, monitor, and analyze any machine data. This book is designed to introduce you quickly to the benefits of using the Splunk Enterprise system. Understanding this technology will allow you to engage with your important data and ensure that it is collected, stored, managed, reported on, and utilized well to enable you to make better business decisions. By equipping you with this knowledge, you will be better prepared to tackle data issues in the fast-paced business world of today. You will learn about various vital topics such as data collection, managing apps, creating reports, and analyzing data using Splunk. You will also be equipped with skills to help you obtain a Twitter API key for use with the Twitter app for Splunk. ...
Splunk is a powerful tool that is used extensively to search, monitor, and analyze any machine data. This book is designed to introduce you quickly to the benefits of using the Splunk Enterprise system. Understanding this technology will allow you to engage with your important data and ensure that it is collected, stored, managed, reported on, and utilized well to enable you to make better business decisions. By equipping you with this knowledge, you will be better prepared to tackle data issues in the fast-paced business world of today. You will learn about various vital topics such as data collection, managing apps, creating reports, and analyzing data using Splunk. You will also be equipped with skills to help you obtain a Twitter API key for use with the Twitter app for Splunk. ...
Machine Learning in Python
Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the co ...
Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the co ...
Learn Swift on the Mac
There's a new language in town. Swift is Apple's new, native, fast, and easy to learn programming language for iOS and OS X app development. It's their "Objective-C without the C". If you are an iOS developer or planning to become one, learning Swift is your #1 priority, and Learn Swift on the Mac tells you everything you need to get up to speed, well, swiftly. You'll start with the Swift Playground and an introduction to object-oriented programming so you can immediately see Swift in action. You then learn about all of the key language features like functions and closures, classes, methods, extensions, and how Swift works just as well as Objective-C when it comes to easy memory management with ARC. Finally you'll learn how to use Swift alongside Objective-C as well as with Core Data, and you'll learn how to put all of the pieces together with a health app using Apple's new HealthKit framework. ...
There's a new language in town. Swift is Apple's new, native, fast, and easy to learn programming language for iOS and OS X app development. It's their "Objective-C without the C". If you are an iOS developer or planning to become one, learning Swift is your #1 priority, and Learn Swift on the Mac tells you everything you need to get up to speed, well, swiftly. You'll start with the Swift Playground and an introduction to object-oriented programming so you can immediately see Swift in action. You then learn about all of the key language features like functions and closures, classes, methods, extensions, and how Swift works just as well as Objective-C when it comes to easy memory management with ARC. Finally you'll learn how to use Swift alongside Objective-C as well as with Core Data, and you'll learn how to put all of the pieces together with a health app using Apple's new HealthKit framework. ...
Building Machine Learning Systems with Python, 2nd Edition
Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems. ...
Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems. ...
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. ...
Machine Learning Projects for .NET Developers
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You'll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you're new to F#, this book will give you everything you need to get started. If you're already familiar with F#, this is your chance to put the language into action in an exciting new context. Along the way, you'll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you. ...
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You'll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you're new to F#, this book will give you everything you need to get started. If you're already familiar with F#, this is your chance to put the language into action in an exciting new context. Along the way, you'll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you. ...
NW.js Essentials
Using Node.js, we can create web applications easily. Now, thanks to NW.js, we can also create desktop apps with it using a unique combination of HTML5 and Node. NW.js is a runtime application based on Chromium and Node.js. In this book, you'll discover how to leverage well-known programming languages, such as JavaScript, HTML, and CSS in order to create NW.js desktop applications. You will implement your first simple application right from the first chapter and see how easy it is to use the platform, after which you will learn about Native UI APIs and the different approaches to Node.js programming. You'll get a complete picture of the many possible ways to package and deploy NW.js applications on Microsoft Windows, Mac OS X, and Linux. So, get ready to explore NW.js and build a real, and complex, application. ...
Using Node.js, we can create web applications easily. Now, thanks to NW.js, we can also create desktop apps with it using a unique combination of HTML5 and Node. NW.js is a runtime application based on Chromium and Node.js. In this book, you'll discover how to leverage well-known programming languages, such as JavaScript, HTML, and CSS in order to create NW.js desktop applications. You will implement your first simple application right from the first chapter and see how easy it is to use the platform, after which you will learn about Native UI APIs and the different approaches to Node.js programming. You'll get a complete picture of the many possible ways to package and deploy NW.js applications on Microsoft Windows, Mac OS X, and Linux. So, get ready to explore NW.js and build a real, and complex, application. ...
Apache Mahout Essentials
Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably. This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains complicated but very effective machine learning algorithms simply, in relation to real-world practical examples. Starting from the fundamental concepts of machine learning and Apache Mahout, this book guides you through Apache Mahout's implementations of machine learning techniques including classification, clustering, and recommendations. During this exciting walkthrough, real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each technique. Finally, you will learn vdata visualization techniques for Apache Mahout to bring your data to life. ...
Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably. This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains complicated but very effective machine learning algorithms simply, in relation to real-world practical examples. Starting from the fundamental concepts of machine learning and Apache Mahout, this book guides you through Apache Mahout's implementations of machine learning techniques including classification, clustering, and recommendations. During this exciting walkthrough, real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each technique. Finally, you will learn vdata visualization techniques for Apache Mahout to bring your data to life. ...
Machine Learning with R, 2nd Edition
Updated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience. With this book, 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. Through full engagement with the sort of real-world problems data-wranglers face, you'll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering. ...
Updated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience. With this book, 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. Through full engagement with the sort of real-world problems data-wranglers face, you'll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering. ...