Showing results for "The English System" in Computers & Technology

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

As organizations shift from monolithic applications to smaller, self-contained microservices, distributed systems have become more fine-grained. But developing these new systems brings its own host of problems. This expanded second edition takes a holistic view of topics that you need to consider when building, managing, and scaling microservices architectures. Through clear examples and practical advice, author Sam Newman gives everyone from architects and developers to testers and IT operators a firm grounding in the concepts.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

(ISC)2 Certified Information Systems Security Professional (CISSP) Official Study Guide, 9th Edition has been completely updated based on the latest 2021 CISSP Exam Outline. This bestselling Sybex study guide covers 100% of the exam objectives. You'll prepare for the exam smarter and faster with Sybex thanks to expert content, knowledge from our real-world experience, advice on mastering this adaptive exam, access to the Sybex online interactive learning environment, and much more. Reinforce what you've learned with key topic exam essentials and chapter review questions.

Want to Implement AI Agents in Your Organization? Heard of Agentic AI & Wonder What It Is About? Need a No-BS Guide to Implementing AI Agents Today? If you answered yes to any of these questions, then keep reading ... Amazon-bestselling author and AI consultant David M. Patel is going to show in this comprehensive hands-on executive guide to AI Agents everything you need to know to implement and harness the full potential of AI Agents & Agentic AI in your organization.

Author Brendan Burns demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. This fully updated second edition includes new chapters on AI inference, AI training, and building robust systems for the real world.

In Democracy In Danger, Braun, a veteran of 3 presidential campaigns and former White House Liaison to the Department of Homeland Security, reveals what the national security apparatus, local election administrators, and political parties have gotten wrong about election security and what America needs to do to protect the ballot box in 2020 and beyond.

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking.

Written by an expert who has created systems ranging from DNA scanners to children's toys, this book is ideal for intermediate and experienced programmers, no matter what platform you use. This expanded second edition includes new chapters on IoT and networked sensors, motors and movement, debugging, data handling strategies, and more.

There are no easy decisions in software architecture. Instead, there are many hard parts—difficult problems or issues with no best practices—that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures. Architecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture.

In this updated edition, the authors show you how zero trust lets you focus on building strong authentication, authorization, and encryption throughout, while providing compartmentalized access and better operational agility. You'll learn the architecture of a zero trust network, including how to build one using currently available technology.

To ensure that applications are reliable and always available, more businesses today are moving applications to AWS. But many companies still struggle to design and build these cloud applications effectively. With this practical guide, software, DevOps, and cloud engineers will learn how to implement resilient designs and configurations in the cloud using hands-on independent labs.

Andrew J. Stewart convincingly shows that emergency software patches and new security products cannot provide the solution to threats such as computer hacking, viruses, software vulnerabilities, and electronic spying. Profound underlying structural problems must first be understood, confronted, and then addressed.

Slow systems are frustrating. They waste time and money. But making consistently great decisions about performance can be easy, if you understand what's going on. This book explains in a clear and thoughtful voice why systems perform the way they do. It's for anybody who's curious about how computer programs and other processes use their time and about what you can do to improve them. Through a mix of personal vignettes and technical use cases, Cary Millsap reviews the process of improving performance and provides best practices for optimizing systems efficiently.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values, and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits, and identify new business opportunities.

As artificial intelligence reshapes the workplace, you face an unprecedented challenge—one this book transforms into an extraordinary opportunity! Whether you're anxious about your future, struggling to harness AI’s potential, leading teams through change, or preparing to become a Human-AI Coach, Dr. Jon Finn reveals a groundbreaking “first principles” approach to supercharging human cognitive performance—just as sports science revolutionized world-champion athletes' physical abilities.

In Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour—from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria—recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.

Stepping Through Cybersecurity Risk Management covers the professional practice of cybersecurity from the perspective of enterprise governance and risk management. It describes the state of the art in cybersecurity risk identification, classification, measurement, remediation, monitoring and reporting.