Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.

Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis.The purpose of this book is to provid...

“For software developers of all experience levels looking to improve their results, and design and implement domain-driven enterprise applications consistently with the best current state of professional practice, Implementing Domain-Driven Design will impart a treasure trove of knowledge hard won within the DDD and enterprise application architecture communities over the last couple decades.”–Randy Stafford, Architect At-Large, Oracle Coherence Product De...

What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explain...

With this practical book, you’ll discover how to catch complications in your distributed system before they develop into costly problems. Based on his extensive experience in systems ops at large technology companies, author Slawek Ligus describes an effective data-driven approach for monitoring and alerting that enables you to maintain high availability and deliver a high quality of service.Learn methods for measuring state changes and data flow in your system, and set up alerts t...

Learn the essence of data science and visualization using R in no time at allKey Features\[\*\]Become a pro at making stunning visualizations and dashboards quickly and without hassle\[\*\]For better decision making in business, apply the R programming language with the help of useful statistical techniques.\[\*\]From seasoned authors comes a book that offers you a plethora of fast-paced techniques to detect and analyze data patterns

Learn how to leverage the power of R for Business IntelligenceKey Features\[\*\] Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful.\[\*\] This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R.\[\*\] Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide.Book Descr...

Object-Oriented Analysis and Design for Information Systems clearly explains real object-oriented programming in practice. Expert author Raul Sidnei Wazlawick explains concepts such as object responsibility, visibility and the real need for delegation in detail. The object-oriented code generated by using these concepts in a systematic way is concise, organized and reusable. The patterns and solutions presented in this book are based in research and industrial applications. You will come a...

Take tiny steps to enter the big world of data science through this interesting guideKey Features\[\*\] Learn the fundamentals of machine learning and build your own intelligent applications\[\*\] Master the art of building your own machine learning systems with this example-based practical guide\[\*\] Work with important classification and regression algorithms and other machine learning techniquesBook DescriptionData scienc...

Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues ...

Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios.The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS ...

Business rules are everywhere. Every enterprise process, task, activity, or function is governed by rules. However, some of these rules are implicit and thus poorly enforced, others are written but not enforced, and still others are perhaps poorly written and obscurely enforced. The business rule approach looks for ways to elicit, communicate, and manage business rules in a way that all stakeholders can understand, and to enforce them within the IT infrastructure in a way that supports the...