Mac eBooks
Clojure for Data Science
The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don't yet exist. Even seas ...
The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don't yet exist. Even seas ...
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. ...
Beginning Ubuntu for Windows and Mac Users
Beginning Ubuntu for Windows and Mac Users is your comprehensive guide to using Ubuntu. You already know how to use a computer running Windows or OS X, but learning a new operating system can feel daunting. If you've been afraid to try Ubuntu because you don't know where to start, this book will show you how to get the most out of Ubuntu for work, home, and play. You'll be introduced to a wide selection of software and settings that will make your computer ready to work for you. Ubuntu makes your computing life easy. Ubuntu's Software Updater keeps all of your software secure and up-to-date. Browsing the Internet becomes faster and safer. Creating documents and sharing with others is built right in. Enjoying your music and movie libraries helps you unwind. ...
Beginning Ubuntu for Windows and Mac Users is your comprehensive guide to using Ubuntu. You already know how to use a computer running Windows or OS X, but learning a new operating system can feel daunting. If you've been afraid to try Ubuntu because you don't know where to start, this book will show you how to get the most out of Ubuntu for work, home, and play. You'll be introduced to a wide selection of software and settings that will make your computer ready to work for you. Ubuntu makes your computing life easy. Ubuntu's Software Updater keeps all of your software secure and up-to-date. Browsing the Internet becomes faster and safer. Creating documents and sharing with others is built right in. Enjoying your music and movie libraries helps you unwind. ...
Learn Swift 2 on the Mac, 2nd Edition
Swift is Apple's new, native, fast, and easy to learn programming language for iOS, watchOS, tvOS 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 2 on the Mac tells you everything you need to get up to speed, well, swiftly. The language is evolving very quickly, Apple has released version 2.1 of the langugae. 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, closures, protocols, 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 REST base application. ...
Swift is Apple's new, native, fast, and easy to learn programming language for iOS, watchOS, tvOS 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 2 on the Mac tells you everything you need to get up to speed, well, swiftly. The language is evolving very quickly, Apple has released version 2.1 of the langugae. 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, closures, protocols, 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 REST base application. ...
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. ...
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. ...
NLTK Essentials
Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, it's becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool. You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text. ...
Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, it's becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool. You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text. ...
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. ...
Understanding Machine Learning
The subject of this book is automated learning, or, as we will more often call it, Machine Learning (ML). That is, we wish to program computers so that they can "learn" from input available to them. Roughly speaking, learning is the process of converting experience into expertise or knowledge. The input to a learning algorithm is training data, representing experience, and the output is some expertise, which usually takes the form of another computer program that can perform some task. Seeking a formal-mathematical understanding of this concept, we'll have to be more explicit about what we mean by each of the involved terms: What is the training data our programs will access? How can the process of learning be automated? How can we evaluate the success of such a process (namely, the quality of the output of a learning program)? ...
The subject of this book is automated learning, or, as we will more often call it, Machine Learning (ML). That is, we wish to program computers so that they can "learn" from input available to them. Roughly speaking, learning is the process of converting experience into expertise or knowledge. The input to a learning algorithm is training data, representing experience, and the output is some expertise, which usually takes the form of another computer program that can perform some task. Seeking a formal-mathematical understanding of this concept, we'll have to be more explicit about what we mean by each of the involved terms: What is the training data our programs will access? How can the process of learning be automated? How can we evaluate the success of such a process (namely, the quality of the output of a learning program)? ...
Mastering Machine Learning with scikit-learn
This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and test data, and evaluating models. You will learn how to use generalized linear models in regression problems, as well as solve problems with text and categorical features. You will be acquainted with the use of logistic regression, regularization, and the various loss functions that are used by generalized linear models. The book will also walk you through an example project that prompts you to label the most uncertain training examples. You will also use an unsupervised Hidden Markov Model to predict stock prices. ...
This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and test data, and evaluating models. You will learn how to use generalized linear models in regression problems, as well as solve problems with text and categorical features. You will be acquainted with the use of logistic regression, regularization, and the various loss functions that are used by generalized linear models. The book will also walk you through an example project that prompts you to label the most uncertain training examples. You will also use an unsupervised Hidden Markov Model to predict stock prices. ...
Learning Cocoa with Objective-C, 4th Edition
Get up to speed on Cocoa and Objective-C, and start developing applications on the iOS and OS X platforms. If you don't have experience with Apple's developer tools, no problem! From object-oriented programming to storing app data in iCloud, the fourth edition of this book covers everything you need to build apps for the iPhone, iPad, and Mac. You'll learn how to work with the Xcode IDE, Objective-C's Foundation library, and other developer tools such as Event Kit framework and Core Animation. Along the way, you'll build example projects, including a simple Objective-C application, a custom view, a simple video player application, and an app that displays calendar events for the user. ...
Get up to speed on Cocoa and Objective-C, and start developing applications on the iOS and OS X platforms. If you don't have experience with Apple's developer tools, no problem! From object-oriented programming to storing app data in iCloud, the fourth edition of this book covers everything you need to build apps for the iPhone, iPad, and Mac. You'll learn how to work with the Xcode IDE, Objective-C's Foundation library, and other developer tools such as Event Kit framework and Core Animation. Along the way, you'll build example projects, including a simple Objective-C application, a custom view, a simple video player application, and an app that displays calendar events for the user. ...