Wiley-VCH - Computer Science

1. Effective Vulnerability Management

   Infuse efficiency into risk mitigation practices by optimizing resource use with the latest best practices in vulnerability management Organizations spend tremendous time and resources addressing vulnerabilities to their technology, software, and organizations. But are those time and resources well spent? Often, the answer is no, because we rely on outdated practices and inefficient, scattershot approaches. Effective Vulnerability Management takes a fresh look at a core component of cybersecurity, revealing the practices, processes, and tools that can enable today's organizations to mitigate risk efficiently and expediently in the era of Cloud, DevSecOps and Zero Trust. Every organization now relies on third-party software and services, ever-changing cloud technologies, and business practices that introduce tremendous potential for risk, requiring constant vigilance. It's more crucial than ever for organizations to successfully minimize the risk to the rest of the organization's success. This book describes the assessment, planning, monitoring, and resource allocation tasks each company must undertake for successful vulnerability management. And it enables readers to do away with unnecessary steps, streamlining the process of securing organizational data and operations. It also covers key emerging domains such as software supply chain security and human factors in cybersecurity. * Learn the important difference between asset management, patch management, and vulnerability management and how they need to function cohesively * Build a real-time understanding of risk through secure configuration and continuous monitoring * Implement best practices like vulnerability scoring, prioritization and design interactions to reduce risks from human psychology and behaviors * Discover new types of attacks like vulnerability chaining, and find out how to secure your assets against them Effective Vulnerability Management is a new and essential volume for executives, risk program leaders, engineers, systems administrators, and anyone involved in managing systems and software in our modern digitally-driven society. [288 Pages, Softcover] Read More...

   
   
   
2. Microsoft SharePoint Premium in the Real World

   Skillfully deploy Microsoft SharePoint Premium to automate your organization's document processing and management In Microsoft SharePoint Premium in the Real World: Bringing Practical Cloud AI to Content Management, a team of veteran Microsoft AI consultants delivers an insightful and easy-to-follow exploration of how to apply Syntex' content AI and advanced machine learning capabilities to your firm's document processing automation project. Using a simple, low-code/no-code approach, the authors explain how you can find, organize, and classify the documents in your SharePoint libraries. You'll learn to use Microsoft SharePoint Premium to automate forms processing, document understanding, image processing, content assembly, and metadata search. Readers will also find: * Strategies for using both custom and pre-built, "off-the-rack" models to build your solutions * The information you need to understand the Azure Cognitive Services ecosystem more fully and how you can use it to build custom tools for your organization * Examples of solutions that will allow you to avoid the manual processing of thousands of your own documents and files An essential and hands-on resource for information managers, Microsoft SharePoint Premium in the Real World is a powerful tool for developers and non-developers alike. [432 Pages, Softcover] Read More...

   
   
   
3. AI-Driven Project Management

   Accelerate your next project with artificial intelligence and ChatGPT In AI-Driven Project Management: Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success, veteran IT and project management advisor Kristian Bainey delivers an insightful collection of strategies for automating the administration and management of projects. In the book, the author focuses on four key areas where project leaders can achieve improved results with AI's data-centric capabilities: minimizing surprises, minimizing bias, increasing standards, and accelerating decision making. You'll also find: * Primers on the role of AI and ChatGPT in Agile, Hybrid, and Predictive approaches to project management * How to accurately forecast a project with ChatGPT * Techniques for crafting impactful AI strategy using AI project management principles Perfect for managers, executives, and business leaders everywhere, AI-Driven Project Management is also a must-read for project management professionals, tech professionals and enthusiasts, and anyone else interested in the intersection of artificial intelligence, machine learning, and project management. [384 Pages, Softcover] Read More...

   
   
   
4. Cognitive Analytics and Reinforcement Learning

   COGNITIVE ANALYTICS AND REINFORCEMENT LEARNING The combination of cognitive analytics and reinforcement learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and reinforcement learning are pivotal branches of artificial intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and machine learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. With a focus on bridging the gap between theory and practice, this book serves as an invaluable resource for researchers and industry professionals seeking to leverage cognitive analytics and reinforcement learning to drive innovation and solve complex problems. The book's real strength lies in bridging the gap between theoretical knowledge and practical implementation. It offers a rich tapestry of use cases and examples. Whether you are a student looking to gain a deeper understanding of these cutting-edge technologies, an AI practitioner seeking innovative solutions for your projects, or an industry leader interested in the strategic applications of AI, this book offers a treasure trove of insights and knowledge to help you navigate the complex and exciting world of cognitive analytics and reinforcement learning. Audience The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with artificial intelligence, data analytics, and cognitive sciences. [384 Pages, Hardcover] Read More...

   
   
   
5. Deep Learning Tools for Predicting Stock Market Movements

   DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: * details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; * explains the rapid expansion of quantum computing technologies in financial systems; * provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; * explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies. [496 Pages, Hardcover] Read More...