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.

The Challenge to AI. The Future of AGI: Bridging Human Cognition and Artificial Intelligence

Mercury Learning and Information, Stephen Robbins

This book invites readers to explore where AI, consciousness, and human cognition intersect. It challenges existing notions in AI and cognitive science by arguing that true intelligence lies not in software but in the brain's complex biochemical system, far removed from current AI architectures. Through examining time, perception, language, and thought, the book presents a compelling case for the indispensability of biology and consciousness in cognition, highlighting the profound differences between man and machine.The journey begins with an introduction to AGI and the brain's resonance, moving through philosophical perspectives on perception and the external world. Readers will delve into the biochemical basis of cognition, exploring implicit and explicit memory, conscious cognition, voluntary actions, and the unique aspects of human speech and generative AI. The book culminates with discussions on affect, space, time, and the requirements for creating a conscious device.Understanding these concepts is crucial for advancing AI and cognitive science. This book transitions readers from conventional views to a new framework that integrates biology and consciousness, blending theory with profound insights. It is an essential resource for those seeking to understand the true nature of intelligence and the future of AI.

Combating Cyberattacks Targeting the AI Ecosystem. Strategies to secure AI systems from emerging cyber threats, risks, and vulnerabilities

Mercury Learning and Information, Aditya K. Sood

Artificial intelligence is transforming industries, but it also exposes organizations to new cyber threats. This course begins by introducing the foundational concepts of securing large language models (LLMs), generative AI applications, and the broader AI infrastructure. Participants will explore the evolving threat landscape, gaining insights into how attackers exploit vulnerabilities in AI systems and the risks posed by trust and compliance failures.The course provides real-world case studies to highlight attack vectors like adversarial inputs, data poisoning, and model theft. Participants will learn practical methods for identifying and mitigating vulnerabilities in AI systems. These insights prepare learners to proactively safeguard their AI infrastructures using advanced security assessment techniques.Finally, the course equips participants with actionable strategies to defend AI systems. You’ll learn to protect sensitive data, implement robust security measures, and address ethical challenges in AI. By the end, you’ll be ready to secure AI ecosystems and adapt to the fast-evolving AI security landscape.

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.

Python 3 and Machine Learning Using ChatGPT / GPT-4. Harness the Power of Python, Machine Learning, and Generative AI

Mercury Learning and Information, Oswald Campesato

This book bridges the gap between theoretical knowledge and practical application in Python programming, machine learning, and using ChatGPT-4 in data science. It starts with an introduction to Pandas for data manipulation and analysis. The book then explores various machine learning classifiers, from kNN to SVMs. Later chapters cover GPT-4's capabilities, enhancing linear regression analysis, and using ChatGPT in data visualization, including AI apps, GANs, and DALL-E.The journey begins with mastering Pandas and machine learning fundamentals. It progresses to applying GPT-4 in linear regression and machine learning classifiers. The final chapters focus on using ChatGPT for data visualization, making complex results accessible and understandable.Understanding these concepts is crucial for modern data scientists. This book transitions readers from basic Python programming to advanced applications of ChatGPT-4 in data science. Companion files with source code, datasets, and figures enhance learning, making this an essential resource for mastering Python, machine learning, and AI-driven data visualization.

Linear Algebra. Learn the Foundations and Applications of Vector Spaces

Mercury Learning and Information, L. Shen, Haohao Wang, J. Wojdylo

This book introduces the fundamental concepts of linear algebra and applies the theorems in computation-oriented applications. It is suitable for a one-semester course and combines definitions and proofs with a focus on computational applications. Examples illustrate the use of software packages such as Mathematica, Maple, and Sage.The journey begins with vector spaces and progresses through linear transformations and operators. It then covers orthogonal bases and matrix decomposition. The material includes a brief introduction to aspects of abstract algebra related to linear algebra, such as groups, rings, modules, fields, and polynomials over fields.Understanding these concepts is crucial for solving complex problems in various fields. This book transitions readers from basic definitions to advanced computational applications, blending theoretical knowledge with practical skills. It is an essential resource for mastering linear algebra and its applications.

Embedded Vision. Mastering Advanced Techniques for Real-Time Image Processing and Analysis

Mercury Learning and Information, S. R. Vijayalakshmi, S. Muruganand

Embedded vision integrates computer vision into machines using algorithms to interpret images or videos. This book serves as an introductory guide for designing vision-enabled embedded products, with applications in AI, machine learning, industrial, medical, automotive, and more. It covers hardware architecture, software algorithms, applications, and advancements in cameras, processors, and sensors.The course begins with an overview of embedded vision, followed by industrial and medical vision applications. It then delves into video analytics, digital image processing, and camera-image sensors. Subsequent chapters cover embedded vision processors, computer vision, and AI integration. The final chapter presents real-time vision-based examples.Understanding these concepts is vital for developing advanced vision-enabled machines. This book takes readers from the basics to advanced topics, blending theoretical knowledge with practical applications. It is an essential resource for mastering embedded vision technology across various industries.

Artificial Intelligence Basics. A Self-Teaching Introduction

Mercury Learning and Information, N. Gupta, R. Mangla

This book is designed as a self-teaching introduction to the fundamental concepts of artificial intelligence (AI). It begins with the history of AI, the Turing test, and early applications, providing a strong foundation. Later chapters cover the basics of searching, game playing, and knowledge representation. The journey continues with detailed explorations of expert systems and machine learning, equipping readers with essential AI techniques.As the course progresses, you will delve into separate programming chapters on Prolog and Python, learning how to implement AI concepts in these languages. These chapters offer practical coding experience, enhancing your understanding of AI programming. The book culminates with a comprehensive chapter on AI machines and robotics, showcasing numerous modern applications and providing a glimpse into the future of AI technology.Understanding these AI concepts is crucial as they form the basis of many modern technologies and applications. This book ensures a smooth transition from a beginner to a proficient AI practitioner, equipped with both theoretical knowledge and practical skills. By the end of the book, you will have a thorough understanding of AI's history, core principles, and practical implementations, ready to apply this knowledge to real-world problems and projects.