Programowanie
Nate Ebel
Using Kotlin without taking advantage of its power and interoperability is like owning a sports car and never taking it out of the garage. While documentation and introductory resources can help you learn the basics of Kotlin, the fact that it’s a new language means that there are limited learning resources and code bases available in comparison to Java and other established languages.This Kotlin book will show you how to leverage software designs and concepts that have made Java the most dominant enterprise programming language. You’ll understand how Kotlin is a modern approach to object-oriented programming (OOP). This book will take you through the vast array of features that Kotlin provides over other languages. These features include seamless interoperability with Java, efficient syntax, built-in functional programming constructs, and support for creating your own DSL. Finally, you will gain an understanding of implementing practical design patterns and best practices to help you master the Kotlin language.By the end of the book, you'll have obtained an advanced understanding of Kotlin in order to be able to build production-grade applications.
Andrew Mallett
Shell scripting is a quick method to prototype a complex application or a problem by automating tasks when working on Linux-based systems. Using both simple one-line commands and command sequences complex problems can be solved with ease, from text processing to backing up sysadmin tools.In this book, you’ll discover everything you need to know to master shell scripting and make informed choices about the elements you employ. Get to grips with the fundamentals of creating and running a script in normal mode, and in debug mode. Learn about various conditional statements' code snippets, and realize the power of repetition and loops in your shell script. Implement functions and edit files using the Stream Editor, script in Perl, program in Python – as well as complete coverage of other scripting languages to ensure you can choose the best tool for your project.
Jose Fernando Almoguera, Reyes Garc?É!!=a Rosado, Sebastian...
Microsoft Silverlight is fully established as a powerful tool for creating and delivering Rich Internet Applications and media experiences on the Web. This book will help you dive straight into utilizing Silverlight 5, which now more than ever is a top choice in the Enterprise for building Business Applications. Mastering LOB Development for Silverlight 5: A Case Study in Action focuses on the development of a complete Silverlight 5 LOB application, helping you to take advantage of the powerful features available along with expert advice. Fully focused on LOB development, this expert guide takes you from the beginning of designing and implementing a Silverlight 5 LOB application, all the way through to completion. Accompanied by a gradually built upon case study, you will learn about data access via RIA and Web services, architecture with MEF and MVVM applied to LOB development, testing and error control, and much more.With Mastering LOB Development for Silverlight 5: A Case Study in Action in hand, you will be fully equipped to expertly develop your own Silverlight Line of Business application, without dwelling on the basics of Enterprise Silverlight development.
Giuseppe Bonaccorso
Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks.By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.
Dr. Saket S.R. Mengle, Maximo Gurmendez
Amazon Web Services (AWS) is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned, and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics and predictive modeling through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.
Cory Lesmeister
Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work.
Gavin Hackeling
Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
Mastering macOS Programming. Hands-on guide to macOS Sierra Application Development
Stuart Grimshaw, Gregory Casamento
macOS continues to lead the way in desktop operating systems, with its tight integration across the Apple ecosystem of platforms and devices. With this book, you will get an in-depth knowledge of working on macOS, enabling you to unleash the full potential of the latest version using Swift 3 to build applications.This book will help you broaden your horizons by taking your programming skills to next level. The initial chapters will show you all about the environment that surrounds a developer at the start of a project. It introduces you to the new features that Swift 3 and Xcode 8 offers and also covers the common design patterns that you need to know for planning anything more than trivial projects. You will then learn the advanced Swift programming concepts, including memory management, generics, protocol orientated and functional programming and with this knowledge you will be able to tackle the next several chapters that deal with Apple’s own Cocoa frameworks. It also covers AppKit, Foundation, and Core Data in detail which is a part of the Cocoa umbrella framework. The rest of the book will cover the challenges posed by asynchronous programming, error handling, debugging, and many other areas that are an indispensable part of producing software in a professional environment.By the end of this book, you will be well acquainted with Swift, Cocoa, and AppKit, as well as a plethora of other essential tools, and you will be ready to tackle much more complex and advanced software projects.