Empirical Cloud Security. A Guide To Practical Intelligence to Evaluate Risks and Attacks

Mercury Learning and Information, Aditya K. Sood

This book, updated to include the latest research and developments in cloud security, is essential for security professionals, DevOps engineers, penetration testers, cloud security engineers, and cloud software developers. It offers practical approaches to securing cloud infrastructure and applications against threats, attacks, and data breaches. The content is refined for better accessibility and engagement, providing a comprehensive guide to cloud security.The course starts with fundamental cloud security concepts and progresses to hands-on assessment techniques based on real-world case studies. It covers cloud architecture, IAM for authentication and authorization, network security, database and storage security, cryptography controls, secure code review, and monitoring and logging. The practical strategies for assessing security and privacy are crucial for building a robust cloud infrastructure.The journey concludes with advanced topics such as privacy in the cloud, identifying security flaws and attacks, and understanding the impact of malicious code. New case studies reveal how threat actors exploit cloud environments, offering preventative measures to enhance cloud security. This structured approach ensures a thorough understanding and practical application of cloud security principles.

The Creation of a Conscious Machine. The AI Quest: Building Awareness with Advanced Artificial Intelligence Technologies

Mercury Learning and Information, Jean E. Tardy

This book delves into Generative AI and the potential for AI to achieve consciousness. It covers historical and modern perspectives on AI, from ancient myths to the Turing Test and current advancements. The book explores the theoretical and practical aspects of creating a conscious AI, including specifications for synthetic consciousness and integrating AI with human cognition. It questions whether generative AI can meet traditional criteria of consciousness.The journey begins with understanding consciousness, tracing AI's origins, and clarifying human cognition through AI. It examines early AI failures, fears of success, and the engineering of consciousness. The book also explores archaic AI representations, the intelligence of automatons, and the relevance of the Turing Test, concluding with strategies for achieving synthetic consciousness.These concepts are crucial for advancing AI towards synthetic consciousness. This book transitions readers from historical perspectives to modern AI challenges, blending theory with practical insights. It is an essential resource for understanding the future of AI and its potential to achieve consciousness.

Navigating the Stock Market. A Practical Guide for Buying, Selling, and AI Risk Management

Mercury Learning and Information, Arshad Khan

This book is perfect for investors, financial analysts, and portfolio managers. It simplifies stock market investing, offering strategies and practical advice for all levels. Key topics include research, buying and selling strategies, and using AI for risk management. The book equips you with essential knowledge and tools for successful stock investing.The course begins with planning, research, and screening, then moves to buying strategies and identifying winning characteristics. It covers company and sector analysis, selling techniques, stock prices, valuation, profitability, market behavior, and technical analysis. Advanced topics include monitoring the economy, market indicators, and avoiding investment mistakes.Understanding these concepts is crucial for informed investment decisions. The final chapters focus on risk management and leveraging AI in stock investing, addressing AI risks and mitigation strategies. This book guides readers from basic to advanced stock market concepts, blending theory with practical skills, making it essential for mastering stock investing.

Google Gemini for Python. Coding with Bard: Mastering Python with Google's AI Tools

Mercury Learning and Information, Oswald Campesato

This book bridges Python 3 programming and Generative AI, equipping readers with the skills to navigate both domains confidently. It starts with Python basics, covering data types, number formatting, text manipulation, loops, functions, data structures, NumPy, Pandas, conditional logic, and reserved words. You'll also learn about handling user input, managing exceptions, and working with command-line arguments.The journey continues into Generative AI, distinguishing it from Conversational AI. It introduces popular platforms and models, including Bard (now called Gemini) and its competitors, providing insights into their capabilities, strengths, weaknesses, and applications. The final chapters show how to generate various Python 3 code samples using Gemini.Understanding these concepts is crucial for modern programming and AI applications. This book transitions readers from basic Python programming to advanced AI techniques, blending theoretical knowledge with practical skills. Companion files with source code and figures enhance the learning experience, making this an essential resource for mastering Python 3 and Generative AI.

Finite Element Analysis. An Introductory Guide to FEM Techniques and Applications

Mercury Learning and Information, Sarhan M. Musa

This comprehensive guide explores the versatility and affordability of Finite Element Analysis (FEA) as a powerful tool for solving engineering problems. The book provides a practical introduction to FEA, covering applications in mechanical, civil, electrical engineering, and physics. It presents a balanced blend of theory and applications, catering to both beginners and those seeking to enhance their FEA skills.The journey begins with mathematical preliminaries and an introduction to the Finite Element Method. It progresses through various applications such as axially loaded members, trusses, beams, stress analysis, thermal analysis, fluid flow analysis, dynamic analysis, and engineering electromagnetics analysis. Each chapter includes comparisons of analytical methods, FEA hand calculations, and software-based solutions, helping readers understand the strengths and limitations of each approach.Understanding these concepts is crucial for effective problem-solving in engineering. This book transitions readers from fundamental principles to advanced engineering applications, blending theoretical knowledge with practical skills. Companion files with executable models and animations enhance the learning experience, making this guide an essential resource for mastering FEA techniques.

Basic Electronics. Theory and Practice

Mercury Learning and Information, Sean Westcott, Jean Riescher Westcott

This updated edition introduces students and hobbyists to electronics, covering microcontrollers, sensors, and wireless communication. Each chapter includes a lab, progressing to building a robot with Arduino and Netduino. New material on Raspberry Pi and Python is included, with companion files featuring videos and code samples.The course begins with basic electronics concepts, building circuits, and understanding components. It covers digital theory and practical applications with sensors, motors, and microcontrollers. Topics include electricity theory, currents, circuits, tools, safety, and components like resistors, capacitors, diodes, and transistors. Advanced topics include power supplies, soldering, digital theory, integrated circuits, memory, and microcontrollers.These concepts are crucial for innovation in electronics. This book transitions readers from basic labs to constructing a robot using open-source hardware. It covers Raspberry Pi projects and explores cybersecurity and IoT. Appendices include math for electronics, a timeline of innovations, careers in electronics, and a glossary. This guide provides both theoretical knowledge and practical skills, making it invaluable for mastering electronics.

Cybersecurity. A Self-Teaching Introduction

Mercury Learning and Information, C. P. Gupta, K. K. Goyal

This book provides fundamental concepts of cybersecurity and cybercrime in an easy-to-understand, self-teaching format. It covers data security, threats, viruses, malicious software, firewalls, VPNs, security architecture, design, policies, cyberlaw, and cloud security.The course starts with an introduction to information systems and cybersecurity application security. It progresses to developing secure information systems and understanding information security policies, standards, and cyberlaw. The final chapters address the security of emerging technologies, including cloud security, IoT, and AES.Understanding these concepts is crucial for protecting data and systems against cyber threats. This book transitions readers from basic knowledge to advanced cybersecurity practices, combining theoretical insights with practical applications. It is an invaluable resource for mastering cybersecurity in today's digital age.

Angular and Machine Learning Pocket Primer. A Comprehensive Guide to Angular and Integrating Machine Learning

Mercury Learning and Information, Oswald Campesato

As part of the best-selling *Pocket Primer* series, this book introduces readers to basic machine learning concepts and integrates them into Angular applications. It offers a fast-paced introduction to essential machine learning features and an overview of popular classifiers. Covering Angular functionality, basic machine learning concepts, and key classification algorithms, the book includes numerous code samples and figures. Topics such as TensorFlow and Keras are also explored.The book begins with a quick introduction to Angular, followed by UI controls, user input, and forms and services. As you progress, you will delve into machine learning, working with classifiers, and integrating TensorFlow.js with Angular. These foundational topics ensure a comprehensive grasp of both Angular and machine learning principles, equipping you with practical skills for developing sophisticated applications.Understanding these concepts is crucial for enhancing Angular projects with machine learning capabilities. This book transitions you from a novice to a proficient developer, equipped with the knowledge and tools needed to create advanced applications. Companion files with source code and color figures enhance the learning experience, making this book an invaluable resource for integrating machine learning with Angular.