Stop Wasting Research
Why do crucial customer insights often fail to drive product decisions? The answer: wasted research. Jake Burghardt identifies the insidious root causes of research waste, giving actionable ideas to increase the impact of siloed research. You'll learn to enhance collaboration, maximize learning, and drive research-informed product launches. Anyone--from UX researchers and insight generators to data scientists and CX analysts--will benefit from these crucial customer insights. Who Should Read This Book This book is for anyone who's seen too many important customer insights that failed to drive next steps in their business. It's for leaders and practitioners who want to experiment with new ways to increase their organization's research use in product development and delivery. Specifically, it's perfect for researchers from any discipline from UX to CX to sales to data science. It's also a must-read for leaders of product, design, marketing, and engineering --anyone who wants to improve decision-making based on available customer research. And that includes operations people. Takeaways Uncover tools and methods to reduce research waste. Learn how to find and use hidden research that might have lasting impact on your organization. Discover knowledge-consolidating tools and requirements for repositories. Increase the impact of any type of customer research on your organization. Note the special "IDEA" sections that show possible actions to choose based on what makes sense for your current resources and organizational context See "You Might Be Asking" sidebars, which give answers to common questions. Search for "Imagine a Way Forward" sidebars that highlight special scenarios--telling a story of action ideas as step-by-step narratives. Look for insightful interviews from experts in the field. Read the chapter summaries of key proposals to get more value from research, including a distillation of what success might look like.
Image Processing, Computer Vision, and Pattern Recognition and Information and Knowledge Engineering
Software Engineering Research and Practice and E-Learning, E-Business, Enterprise Information Systems, and E-Government
Interpretability and Explainability in AI Using Python
Demystify AI Decisions and Master Interpretability and Explainability Today Book DescriptionInterpretability in AI/ML refers to the ability to understand and explain how a model arrives at its predictions. It ensures that humans can follow the model's reasoning, making it easier to debug, validate, and trust. Interpretability and Explainability in AI Using Python takes you on a structured journey through interpretability and explainability techniques for both white-box and black-box models. You'll start with foundational concepts in interpretable machine learning, exploring different model types and their transparency levels. As you progress, you'll dive into post-hoc methods, feature effect analysis, anchors, and counterfactuals-powerful tools to decode complex models. The book also covers explainability in deep learning, including Neural Networks, Transformers, and Large Language Models (LLMs), equipping you with strategies to uncover decision-making patterns in AI systems. Through hands-on Python examples, you'll learn how to apply these techniques in real-world scenarios. By the end, you'll be well-versed in choosing the right interpretability methods, implementing them efficiently, and ensuring AI models align with ethical and regulatory standards-giving you a competitive edge in the evolving AI landscape. Table of Contents1. Interpreting Interpretable Machine Learning2. Model Types and Interpretability Techniques3. Interpretability Taxonomy and Techniques4. Feature Effects Analysis with Plots5. Post-Hoc Methods6. Anchors and Counterfactuals7. Interpretability in Neural Networks8. Explainable Neural Networks9. Explainability in Transformers and Large Language Models10. Explainability and Responsible AI Index
Fundamentals of Digital Forensics
This textbook describes the theory and methodology of digital forensic examinations, presenting examples developed in collaboration with police authorities to ensure relevance to real-world practice. The coverage includes discussions on forensic artifacts and constraints, as well as forensic tools used for law enforcement and in the corporate sector. Emphasis is placed on reinforcing sound forensic thinking, and gaining experience in common tasks through hands-on exercises.This enhanced third edition describes practical digital forensics with open-source tools and includes an outline of current challenges and research directions.Topics and features: Outlines what computer forensics is, and what it can do, as well as what its limitations areDiscusses both the theoretical foundations and the fundamentals of forensic methodologyReviews broad principles that are applicable worldwideExplains how to find and interpret several important artifactsDescribes free and open-source software toolsFeatures content on corporate forensics, ethics, SQLite databases, triage, and memory analysisIncludes new supporting video lectures on YouTubeThis easy-to-follow primer is an essential resource for students of computer forensics, and will also serve as a valuable reference for practitioners seeking instruction on performing forensic examinations.
Optimal Spending on Cybersecurity Measures
Optimal Spending on Cybersecurity Measures: AI and Governance introduces the cyber risk investment model, and the cybersecurity risk management framework used within business-driven risk assessments to address government regulations, industry standards and applicable Laws.
Biometric Technology and Authentication
Biometric Technology & Authentication is an update to the first edition of this book. Some of the updates include newer images, and an extensive review as to how both the AWS and Microsoft Azure can be used to host a Biometrics In The Cloud Infrastructure, which will be a hot topic going into 2025 and beyond.
Internet Computing and Iot and Embedded Systems, Cyber-Physical Systems, and Applications
AI-Powered Social Media Marketing 2025
Explore the revolutionary impact of AI on social media marketing and discover key trends that are shaping the future. From automating content creation and audience engagement to optimizing advertising strategies, this resource provides actionable insights to elevate your marketing game. Understand why integrating AI is crucial for generating income online and learn how businesses and creators are monetizing their social platforms effectively. Discover essential AI tools designed to streamline your marketing efforts, enhance customer engagement, and analyze performance metrics. With a focus on practical applications, you will learn how to automate tasks, create compelling content, and use data-driven insights to refine your strategies. Whether you are an entrepreneur, marketer, or content creator, these insights will empower you to make smarter decisions and boost your earnings. Delve into platform-specific strategies for maximizing profits on popular social media channels. Gain insights on how to optimize your presence on Facebook, Instagram, TikTok, and more by utilizing AI to drive engagement, enhance targeting, and increase conversion rates. With practical tips and techniques, you will learn how to monetize your efforts through ads, e-commerce, influencer marketing, and more.In addition to practical applications, this guide addresses the ethical considerations of using AI in social media marketing. Understand the importance of data privacy and transparency in building trust with your audience, ensuring long-term loyalty and success. Prepare to unlock new revenue streams and elevate your marketing strategy by embracing the potential of AI in social media. This comprehensive resource equips you with the knowledge and tools necessary to navigate the evolving landscape of digital marketing, ensuring you remain competitive and profitable. Embrace AI, transform your marketing efforts, and achieve the success you've always envisioned.
Optimal Spending on Cybersecurity Measures
Optimal Spending on Cybersecurity Measures: AI and Governance introduces the cyber risk investment model, and the cybersecurity risk management framework used within business-driven risk assessments to address government regulations, industry standards and applicable Laws.
Optimal Spending on Cybersecurity Measures
Optimal Spending on Cybersecurity Measures: Third Party Risk Management introduces the cyber risk investment model, and the cybersecurity risk management framework used within business-driven risk assessments to address government regulations, industry standards and applicable Laws.
Optimal Spending on Cybersecurity Measures
Optimal Spending on Cybersecurity Measures: Third Party Risk Management introduces the cyber risk investment model, and the cybersecurity risk management framework used within business-driven risk assessments to address government regulations, industry standards and applicable Laws.
Multilingual Artificial Intelligence
Multilingual Artificial Intelligence is a guide for non-computer science specialists and learners looking to explore the implementation of AI technologies to solve real-life problems involving language data.
Security Issues in Communication Devices, Networks and Computing Models
In summary, addressing security issues in communication devices, networks, and computing models is fundamental to the successful implementation of Industry 5.0. It not only protects the assets and operations of organizations but also contributes to the overall safety, reliability, and sustainability of advanced industrial systems.
The Music Producer's Guide to Social Media Content
The Music Producer's Guide to Social Media Content offers essential insights into the role of audio in content creation for social media platforms. It provides advice on succeeding in the music industry through the successful adoption of social media practices, and creating high quality content as a vehicle of career growth.
Spring System Design in Practice
Transform raw requirements into scalable, resilient web applications with Spring, and build secure, high-performance systems from the ground up using expert guidance and best practicesKey Features: - Establish yourself as the go-to person for strategic decision-making and solutions design with proven strategies- Write clean, modular, and testable code with the power of dependency injection- Optimize your development efforts by artfully connecting diverse use cases with the right Spring components- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Software system design goes beyond just writing code-it requires a structured approach to translating real-world requirements into scalable, maintainable solutions. With Rodrigo Santiago's hands-on mentoring style and Java Spring expertise, he makes system design accessible to developers at all levels.Spring System Design in Practice guides you through building robust software architectures with Spring. From breaking down complex business needs into actionable use cases to implementing services using Spring Boot, this book equips you with the tools and best practices needed for developing secure, high-performance applications. You'll explore inter-service communication, security, and aspect-oriented programming to streamline development. Covering microservices architecture, the book demonstrates how to create self-configuring, resilient, and event-driven services that integrate seamlessly into the cloud. Through hands-on experience, you'll apply best practices to enhance reliability and scalability while tackling complex challenges such as state management, resilience patterns, concurrency issues, and distributed transactions-including bottlenecks related to asynchronous and reactive programming.By the end of this book, you'll have the confidence to analyze system requirements and design well-structured, scalable architectures.What You Will Learn: - Implement microservices for scalable, resilient web systems- Break down business goals into well-structured product requirements- Weigh tradeoffs between writing asynchronous vs. synchronous services and SQL vs. NoSQL storage- Accelerate service development and reliability through the adoption of test-driven development- Identify and eliminate hidden performance bottlenecks to maximize speed and efficiency- Achieve real-time processing and responsiveness in distributed environmentsWho this book is for: If you're an entry-level IT professional with junior to mid-level Java and Spring experience, this pragmatic guide will fast-track your journey to mastering the Spring ecosystem. Designed to accelerate your career path toward becoming a senior software engineer, system architect, technical lead, or aspiring CTO, it provides clear explanations of the Spring ecosystem and its intricate patterns.For experienced developers or architects, this book offers essential insights and hands-on knowledge to deepen your architectural skills and design resilient web systems.Table of Contents- What Are Product Requirements?- Sorting Complex Requirements into Features, Use Cases, and Stories- Defining Domains for Your Application - Defining Services for Your Domains - Writing Your Services - Introducing REST APIs with the Spring Framework- Translating Business Requirements into Well-Designed Spring APIs- Handling Data and Evolving Your Microservice- Securing Services with Spring Security and OAuth 2.0- High-Performance Secure Communication Between Spring Services- Building Asynchronous, Event-Driven Systems With NoSQL Databases(N.B. Please use the Read Sample option to see further chapters)
Safety Assurance under Uncertainties
Modern software systems operate under an unprecedented degree of uncertainties, making them hard to specify, model, test, analyze, and verify. Safety assurance of such systems requires efforts that unite different disciplines such as formal methods, software science, software engineering, control theory, machine learning.
Guardians of Data
This book helps to reduce risks of data loss by monitoring and controlling the flow of sensitive data via the network, email or web. This book also shows the guidance about data protection that data is not corrupted, is accessible for authorized purposes only, and is in compliance with applicable legal or regulatory requirements.
Security Issues in Communication Devices, Networks and Computing Models
In summary, addressing security issues in communication devices, networks, and computing models is fundamental to the successful implementation of Industry 5.0. It not only protects the assets and operations of organizations but also contributes to the overall safety, reliability, and sustainability of advanced industrial systems.
Recent Advances in Internet of Things Security
Recent Advances in Internet of Things Security discusses the critical importance of robust security frameworks to protect Internet of Things ecosystems against various cyber threats. It highlights the security risks associated with Internet of Things devices and applications and present a variety of potential solutions.
Guardians of Data
This book helps to reduce risks of data loss by monitoring and controlling the flow of sensitive data via the network, email or web. This book also shows the guidance about data protection that data is not corrupted, is accessible for authorized purposes only, and is in compliance with applicable legal or regulatory requirements.
A Cybersecurity Leader's Journey
A Cybersecurity Leader's Journey: Speaking the Language of the Board equips leaders with the skills to translate technical expertise into business-savvy communication that builds trust and drives informed decision-making.
Building Agentic AI Systems
Master the art of building AI agents with large language models using the coordinator, worker, and delegator approach for orchestrating complex AI systemsKey Features: - Understand the foundations and advanced techniques of building intelligent, autonomous AI agents- Learn advanced techniques for reflection, introspection, tool use, planning, and collaboration in agentic systems- Explore crucial aspects of trust, safety, and ethics in AI agent development and applications- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Gain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks.Starting with the foundations of GenAI and agentic architectures, you'll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents.Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention.What You Will Learn: - Master the core principles of GenAI and agentic systems- Understand how AI agents operate, reason, and adapt in dynamic environments- Enable AI agents to analyze their own actions and improvise- Implement systems where AI agents can leverage external tools and plan complex tasks- Apply methods to enhance transparency, accountability, and reliability in AI- Explore real-world implementations of AI agents across industriesWho this book is for: This book is ideal for AI developers, machine learning engineers, and software architects who want to advance their skills in building intelligent, autonomous agents. It's perfect for professionals with a strong foundation in machine learning and programming, particularly those familiar with Python and large language models. While prior experience with generative AI is beneficial, the book covers foundational concepts for those new to agentic systems.Table of Contents- Fundamentals of Generative AI- Principles of Agentic Systems- Essential Components of Intelligent Agents- Reflection and Introspection in Agents- Enabling Tool Use and Planning in Agents- Exploring the Coordinator, Worker, and Delegator Approach- Effective Agentic System Design Techniques- Building Trust in Generative AI Systems- Managing Safety and Ethical Considerations- Common Use Cases and Applications- Conclusion and Future Outlook
