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...

Uncover hidden patterns of data and respond with countermeasuresSecurity professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach w...

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...

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software.This book will help you:Become a contr...

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...

Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data. Explore each of the major data mining algorithms, including naive bayes, decision trees, time series, clustering, association rules, and neural networks. Learn more about topics like mining OLAP databases, data mining with SQL...