Agile continues to be the most adopted software development methodology among organizations worldwide, but it generally hasn't integrated well with traditional security management techniques. And most security professionals aren’t up to speed in their understanding and experience of agile development. To help bridge the divide between these two worlds, this practical guide introduces several security tools and techniques adapted specifically to integrate with agile development.
Written by security experts and agile veterans, this book begins by introducing security principles to agile practitioners, and agile principles to security practitioners. The authors also reveal problems they encountered in their own experiences with agile security, and how they worked to solve them.
You’ll learn how to:
Add security practices to each stage of your existing development lifecycle
Integrate security with planning, requirements, design, and at the code level
Include security testing as part of your team’s effort to deliver working software in each release
Implement regulatory compliance in an agile or DevOps environment
Build an effective security program through a culture of empathy, openness, transparency, and collaboration
The Book of R: A First Course in Programming and Statistics
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical...
Learn Python Visually
Learn Python Visually is a modern breakthrough that makes learning programming more intuitive, easier, and fun. Using the most basic approach to learning that we all inherently know from childhood, "Learn Python VISUALLY" solves the comprehension problem that so many other books cannot seem to bridge. Visual learners retain...
Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We...
Learning Node: Moving to the Server-Side
Advanced Analytics with Spark: Patterns for Learning from Data at Scale
In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.
You’ll start with an...