Verleger: 16
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.
Cory Lesmeister
This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do.With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.
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 Machine Learning with Spark 2.x. Harness the potential of machine learning, through spark
Michal Malohlava, Alex Tellez, Max Pumperla
The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment.
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.
Bret Williams, Jonathan Bownds
The long-awaited release of the world's most popular online solution, Magento 2, is now out with an all new interface and several enhancements. This book offers you advanced guidance on managing, optimizing, and extending your store while taking advantage of the new features of Magento 2.This is a comprehensive guide to using the all new features and interface of Magento 2 to build, extend, and design online stores. From planning your Magento installation through to advanced techniques designed to make your store as successful as possible, this book is your roadmap to managing your Magento store. Focusing on Magento's Community version, the book covers everything from creating and managing multiple stores to fine-tuning Magento for speed and performance. You’ll learn how to manage categories, products, design themes, extensions, and more.
