Sasha Denning doesn’t ask for anything—ever. Feeling unappreciated and stuck in a crumbling marriage with her husband, Mark, she’s suddenly given a dramatic escape: a near-death experience. Returning to life with a mission to help others, Sasha is thrust into a series of challenges that range from comical to heart-wrenching.Zinnia, her determined but rule-bound trainee spirit guide, wants to help Sasha mend her life and marriage. But with The Spirit Guidance Rule Book restricting h...

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...

With the award-winning book Agile Software Development: Principles, Patterns, and Practices, Robert C. Martin helped bring Agile principles to tens of thousands of Java and C++ programmers. Now .NET programmers have a definitive guide to agile methods with this completely updated volume from Robert C. Martin and Micah Martin, Agile Principles, Patterns, and Practices in C#.This book presents a series of case studies illustrating the fundamentals o...

The only security book to be chosen as a Dr. Dobbs Jolt Award Finalist since Bruce Schneier's Secrets and Lies and Applied Cryptography!Adam Shostack is responsible for security development lifecycle threat modeling at Microsoft and is one of a handful of threat modeling experts in the world. Now, he is sharing his considerable expertise into this unique book. With pages of specific actionable advice, he details how to build better security into t...

Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

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...

Within the framework of Acceptance Test-Driven-Development (ATDD), customers, developers, and testers collaborate to create acceptance tests that thoroughly describe how software should work from the customer’s viewpoint. By tightening the links between customers and agile teams, ATDD can significantly improve both software quality and developer productivity.   This is the first start-to-finish, real-world guide to ...

Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with JavaKey Features\[\*\] Go beyond the theory and put Deep Learning into practice with Java\[\*\]Find out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and Caffe\[\*\] Whether you’re a data scientist or Java developer, dive in and find out how to ta...

This book is written for the test analyst who wants to achieve advanced skills in test analysis, design, and execution. With a hands-on, exercise-rich approach, this book teaches you how to define and carry out the tasks required to put a test strategy into action.Learn how to analyze the system, taking into account the user’s quality expectations. Additionally, learn how to evaluate system requirements as part of formal and informal reviews, using an understanding...

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...

Master alternative Big Data technologies that can do what Hadoop can't: real-time analytics and iterative machine learning.When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn't well suited for, especially real-time analytics and contexts requiring the use of iterative machine learning algorithms. Fortunately, several powerful new technologies have been developed specifically for use ...

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