MLI Generative AI Series

This book provides a bridge between the worlds of Python 3 programming and Generative AI, aiming to equip readers with the skills to navigate both domains with confidence. It begins with an introduction to fundamental aspects of Python programming, which include various data types, number formatting, Unicode and UTF-8 handling, and text manipulation techniques. In addition, you will learn about loops, functions, data structures, NumPy, Pandas, conditional logic, and reserved words in Python. Further chapters show how to handle user input, manage exceptions, and work with command-line arguments. The text then transitions to the realm of Generative AI, discussing its distinction from Conversational AI. Popular platforms and models, including Bard (now called “Gemini”) and its competitors, are presented to give readers an understanding of the current AI landscape. The book discusses the capabilities of Bard, its strengths, weaknesses, and potential applications. Finally, you will learn how to generate a variety of Python 3 code samples via Bard.

1. Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges.
2. Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn.

This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were generated by ChatGPT and GPT-4. Chapter 1 provides an overview of ChatGPT and GPT-4, followed by a chapter which contains Python 3.x code samples for solving various programming tasks in Python. Chapter 3 contains code samples for data visualization, and Chapter 4 contains code samples for linear regression. The final chapter covers visualization with Gen AI (Generative AI) and DALL-E. Companion files with source code and figures are available for downloading.

• Encourages readers to compare and contrast hand-written code with ChatGPT-generated code. This approach fosters discussions on code efficiency, readability, and maintainability, enhancing understanding of programming paradigms and techniques.

This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understanding recursion, strings, arrays, fundamental data structures, algorithm analysis, queues and stacks, and follows with the role of ChatGPT in generating, explaining, and debugging code. Companion files with source code and figures available for downloading. It’s an essential resource for those starting Java programming and for anyone curious about the applications of ChatGPT in coding.

1. Describes seven novel variations of the Turing test.
2. Outlines an original definition of consciousness described as implementable specifications.
3. Introduces the concept of Mathematics as a "genetically" transmissible cognitive medium.

This book presents a groundbreaking journey into the world of Generative AI technology and offers an in-depth look at the prospect of AI achieving consciousness. The book navigates through various historical and modern perspectives on AI, from ancient myths to the Turing Test to the latest in technological advancements. It covers the theoretical and practical aspects of creating a conscious AI, including the specifications for synthetic consciousness and the integration of AI with human cognition. The book questions whether generative AI can meet the traditional criteria of consciousness and how this might be realized.

This book is intended primarily for people who want to learn both Python 3 and how to use ChatGPT with Python. Chapter One begins with an introduction to fundamental aspects of Python programming, including various data types, number formatting, Unicode and UTF-8 handling, and text manipulation techniques. Later, the book covers loops, conditional logic, and reserved words in Python. You will also see how to handle user input, manage exceptions, and work with command-line arguments. Next, the text transitions to the realm of Generative AI, discussing its distinction from Conversational AI. Popular platforms and models, including ChatGPT, GPT-4, and their competitors, are presented to give readers an understanding of the current AI landscape. The book also sheds light on the capabilities of ChatGPT, its strengths, weaknesses, and potential applications. In addition, you will learn how to generate a variety of Python 3 code samples via ChatGPT using the “Code Interpreter” plugin. Code samples and figures from the book are available for downloading. In essence, the book provides a modest bridge between the worlds of Python programming and AI, aiming to equip readers with the knowledge and skills to navigate both domains confidently.

This book is designed to show readers the concepts of Python 3 programming and the art of data visualization. It also explores cutting-edge techniques using ChatGPT/GPT-4 in harmony with Python for generating visuals that tell more compelling data stories. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic data types, loops, and functions to more advanced constructs like dictionaries, sets, and matrices. In Chapter 2, the focus shifts to NumPy and its powerful array operations, leading into data visualization using prominent libraries such as Matplotlib. Chapter 6 includes Seaborn's rich visualization tools, offering insights into datasets like Iris and Titanic. Further, the book covers other visualization tools and techniques, including SVG graphics, D3 for dynamic visualizations, and more. Chapter 7 covers information about the main features of ChatGPT and GPT-4, as well as some of their competitors. Chapter 8 contains examples of using ChatGPT in order to perform data visualization, such as charts and graphs that are based on datasets (e.g., the Titanic dataset). Companion files with code, datasets, and figures are available for downloading. From foundational Python concepts to the intricacies of data visualization, this book is ideal for Python practitioners, data scientists, and anyone in the field of data analytics looking to enhance their storytelling with data through visuals. It's also perfect for educators seeking material for teaching advanced data visualization techniques.

This book provides a comprehensive group of topics covering the details of the Transformer architecture, BERT models, and the GPT series, including GPT-3 and GPT-4. Spanning across ten chapters, it begins with foundational concepts such as the attention mechanism, then tokenization techniques, explores the nuances of Transformer and BERT architectures, and culminates in advanced topics related to the latest in the GPT series, including ChatGPT. Key chapters provide insights into the evolution and significance of attention in deep learning, the intricacies of the Transformer architecture, a two-part exploration of the BERT family, and hands-on guidance on working with GPT-3. The concluding chapters present an overview of ChatGPT, GPT-4, and visualization using generative AI. In addition to the primary topics, the book also covers influential AI organizations such as DeepMind, OpenAI, Cohere, Hugging Face, and more. Readers will gain a comprehensive understanding of the current landscape of NLP models, their underlying architectures, and practical applications. Features companion files with numerous code samples and figures from the book.

Unlock data-driven decision-making with Business Intelligence and Data Analysis in the Age of AI. This guide combines traditional BI with AI’s transformative power to help professionals and newcomers excel in the data era. Whether you're a seasoned professional or new to BI, this book provides actionable strategies to navigate the complexities of modern data analysis. Embark on this illuminating journey to master the tools, strategies, and ethical considerations that define modern business intelligence and AI.
FEATURES

• BI Fundamentals: Master analytics processes and tools
• Ethical and Regulatory Challenges: Navigate governance, security, privacy, and ethical frameworks
• BI Tools: Learn the power of tools like R, SQL, Python, and data manipulation techniques
• Visualize and Predict: Learn data visualization and predictive analytics to forecast trends and drive innovation
• Embrace the Future: Discover how AI transforms BI, unlocking new opportunities and navigating emerging risks.

In a world increasingly shaped by data and artificial intelligence, the ethical challenges surrounding data use have never been more critical. Data Ethics in the Age of AI provides a compelling exploration of the moral, legal, and societal dimensions of data in the digital era.
This insightful book delves into key issues such as privacy, algorithmic bias, transparency, and accountability, offering readers a robust framework for navigating the complex intersection of technology and ethics. With real-world examples and thought-provoking discussions, it equips business leaders, policymakers, researchers, and students with the knowledge and tools to foster ethical responsibility in the face of rapid technological advancements.
Discover how we can build a future where data is used responsibly, equitably, and for the greater good. Data Ethics in the Age of AI is your essential guide to understanding and shaping the ethical landscape of our data-driven world.

This book is a comprehensive guide designed to teach the fundamentals of Python programming while introducing the exciting possibilities of Generative AI. Whether you’re a novice or a developer looking to integrate Claude 3 into your workflow, this book offers a clear, step-by-step path to mastering Python and leveraging AI-driven code generation. It begins by covering Python fundamentals, including data types, string manipulation, loops, conditional logic, and exception handling. It then introduces Python collections, such as lists, dictionaries, and sets, along with their practical applications. Readers will explore essential Python libraries like NumPy and Pandas, learning how to manipulate data and perform advanced operations. The last two chapters cover Generative AI and Claude, distinguishing it from conversational AI and provides hands-on examples of Claude-generated Python code to solve various programming tasks. Readers will find a balanced mix of theory, practical examples, and Claude-generated code to build both foundational programming skills and an understanding of AI-driven development.
FEATURES
• Covers Python programming basics and popular libraries like NumPy and Pandas, with a focus on practical applications
• Introduces Generative AI concepts and Claude, showcasing its use in generating Python code
• Includes companion files with code and images -- available from the publisher for downloading (with proof of purchase)

This book is a comprehensive guide designed to teach the fundamentals of Python programming while introducing the exciting possibilities of Generative AI. Whether you’re a novice or a developer looking to integrate Grok into your workflow, this book offers a clear, step-by-step path to mastering Python and leveraging AI-driven code generation. It begins by covering Python fundamentals, including data types, string manipulation, loops, conditional logic, and exception handling. It then introduces Python collections, such as lists, dictionaries, and sets, along with their practical applications. Readers will explore essential Python libraries like NumPy and Pandas, learning how to manipulate data and perform advanced operations. The last two chapters cover Generative AI and Grok, distinguishing it from conversational AI and provides hands-on examples of Grok-generated Python code to solve various programming tasks. Readers will find a balanced mix of theory, practical examples, and Grok-generated code to build both foundational programming skills and an understanding of AI-driven development.
FEATURES
• Covers Python programming basics and popular libraries like NumPy and Pandas, with a focus on practical applications
• Introduces Generative AI concepts and Grok, showcasing its use in generating Python code
• Includes companion files with code and images -- available from the publisher for downloading (with proof of purchase)

This book offers a thorough exploration of Large Language Models (LLMs), guiding developers through the evolving landscape of generative AI and equipping them with the skills to utilize LLMs in practical applications. Designed for developers with a foundational understanding of machine learning, this book covers essential topics such as prompt engineering techniques, fine-tuning methods, attention mechanisms, and quantization strategies to optimize and deploy LLMs. Beginning with an introduction to generative AI, the book explains distinctions between conversational AI and generative models like GPT-4 and BERT, laying the groundwork for prompt engineering (Chapters 2 and 3). Some of the LLMs that are used for generating completions to prompts include Llama-3.1 405B, Llama 3, GPT-4o, Claude 3, Google Gemini, and Meta AI. Readers learn the art of creating effective prompts, covering advanced methods like Chain of Thought (CoT) and Tree of Thought prompts. As the book progresses, it details fine-tuning techniques (Chapters 5 and 6), demonstrating how to customize LLMs for specific tasks through methods like LoRA and QLoRA, and includes Python code samples for hands-on learning. Readers are also introduced to the transformer architecture’s attention mechanism (Chapter 8), with step-by-step guidance on implementing self-attention layers. For developers aiming to optimize LLM performance, the book concludes with quantization techniques (Chapters 9 and 10), exploring strategies like dynamic quantization and probabilistic quantization, which help reduce model size without sacrificing performance.
FEATURES
• Covers the full lifecycle of working with LLMs, from model selection to deployment
• Includes code samples using practical Python code for implementing prompt engineering, fine-tuning, and quantization
• Teaches readers to enhance model efficiency with advanced optimization techniques
• Includes companion files with code and images -- available from the publisher

This book is a guide to navigating the evolving landscape of artificial intelligence. Designed for both novices and seasoned professionals it covers a broad range of topics from fundamental ideas to innovative advancements. Readers will investigate the principles of machine learning, explore the intricacies of deep learning architectures, and discover the applications of natural language processing and computer vision. With its concise explanations and useful examples, it gives readers the knowledge and abilities they need to confidently traverse the changing field of artificial intelligence. This text also looks at real-world case studies and important ethical issues, providing insightful information about the ethical ramifications and societal effects of technology.

Features:

• Practical applications and case studies with a section on use cases across various industries, including healthcare, finance, transportation, and retail.
• Actionable steps for getting started with AI include how to set up an AI development environment, learning Python for AI applications, and utilizing popular AI libraries.
• Resources for further study including, AI online courses, AI communities and forums, and recommended books essentially, a roadmap for continuous learning.

This book provides an introduction to generative AI and how to use Perplexity to generate graphics code using various combinations of HTML, CSS3, and SVG. It covers various aspects of modern web development and AI technologies, with a particular emphasis on Generative AI, CSS3, SVG, JavaScript, HTML, and popular web features like 3D animations and gradients. By exploring these topics, readers will gain a deeper understanding of how AI can enhance web development processes and how to leverage AI models like Perplexity to streamline development workflows. Web developers, UI/UX designers, and software engineers seeking to blend traditional web development skills with the latest AI technologies will find this book to be a valuable resource.

This book describes the AI tools in concept and how they apply directly to project success. It also demonstrates the strategy and methods used to purchase and implement AI tools for project management. You will understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using artificial intelligence for project management improves project success rates. The book features project management success stories and demonstrates how to leave behind that low project success rate for one that is 95 percent or higher. Supplemental teaching materials are available for use as a textbook.

This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. Companion files with code, figures, and datasets are available for downloading from the publisher.

This book explores the synergy between Claude3, a cutting-edge AI model, and Web technologies such as HTML, CSS3, and SVG, providing both novices and experienced developers with the tools to create visually stunning Web graphics and animations. It introduces the fundamental concepts of Generative AI, the key players in the field, and the distinctive features of Claude3, while also mastering the art of prompt engineering to interact effectively with AI models. The book covers creating dynamic 3D animations with CSS3, including effects like glowing, image fading, and rotating, and demonstrates how to leverage Claude3 to generate sophisticated SVG graphics and animations, thereby enhancing Web designs with advanced visual effects.

FEATURES

• Covers generative AI fundamentals to advanced CSS3 and SVG techniques, offering comprehensive material on modern web development technologies
• Features both manually created and AI generated code samples, security issues, crafting prompts, and accessibility needs
• Balances theoretical knowledge and practical examples, so readers gain hands-on experience in implementing AI-driven design solutions using Claude-generated code
• Includes companion files with code, datasets, and images from the book -- available from the publisher for downloading (with proof of purchase)

TABLE OF CONTENTS

1: The Generative AI Landscape.
2: Prompt Engineering.
3: Introduction to CSS3.
4: CSS3 3D Animation.
5: CSS3 and Claude 3.
6: Introduction to SVG.
7: SVG and Claude 3. Index.

In today's dynamic marketing landscape, artificial intelligence (AI) stands at the forefront of innovation, offering unprecedented opportunities for marketers. This book enables marketing professionals to harness the power of AI, featuring in-depth discussions on key topics such as generative AI, personalized customer experiences, team and workflow augmentation, and data analysis optimization. It is divided into four parts, each addressing a different aspect of AI and marketing. Part I covers the fundamentals of AI in marketing, including machine learning and generative AI. Part II explores growth areas for marketing and AI, using generative AI and customer journey personalization. Part III goes into detail about how to use AI, particularly generative AI tools, to enhance the marketing function. Part IV is about integration and optimization, providing insights on when and where to invest in AI and how to prepare your team for an AI-driven marketing future.

This book is designed to equip you with the knowledge and skills necessary to navigate the intersection of web development and artificial intelligence (AI). It covers various aspects of modern web development and AI technologies, with a particular emphasis on Generative AI, CSS3, SVG, JavaScript, HTML, and popular web features like 3D animations and gradients. By exploring these topics, readers will gain a deeper understanding of how AI can enhance web development processes and how to leverage AI models like Google Gemini to streamline development workflows. Web developers, UI/UX designers, and software engineers seeking to blend traditional web development skills with the latest AI technologies will find this book to be a valuable resource.

This book is designed to equip you with the knowledge and skills necessary to navigate the intersection of web development and artificial intelligence (AI). It covers various aspects of modern web development and AI technologies, with a particular emphasis on Generative AI, CSS3, SVG, JavaScript, HTML, and popular web features like 3D animations and gradients. By exploring these topics, readers will gain a deeper understanding of how AI can enhance web development processes and how to leverage AI models like GPT-4 to streamline development workflows. Web developers, UI/UX designers, and software engineers seeking to blend traditional web development skills with the latest AI technologies will find this book to be a valuable resource.

This book is designed to bridge the gap between theoretical knowledge and practical application in the fields of Python programming, machine learning, and the innovative use of ChatGPT-4 in data science. The book is structured to facilitate a deep understanding of several core topics. It begins with a detailed introduction to Pandas, a cornerstone Python library for data manipulation and analysis. Next, it explores a variety of machine learning classifiers from kNN to SVMs. In later chapters, it discusses the capabilities of GPT-4, and how its application enhances traditional linear regression analysis. Finally, the book covers the innovative use of ChatGPT in data visualization. This segment focuses on how AI can transform data into compelling visual stories, making complex results accessible and understandable. It includes material on AI apps, GANs, and DALL-E. Companion files are available for downloading with code and figures from the text.

• Comprehensive guide to prompt engineering for ChatGPT, covering foundational principles and advanced techniques.
• Real-world examples and case studies showcasing the impact of well-crafted prompts

This book provides a structured framework for exploring various aspects of prompt engineering for ChatGPT, from foundational principles to advanced techniques, real-world applications, and ethical considerations. It aims to guide readers in effectively harnessing the capabilities of ChatGPT through well-crafted prompts to achieve their goals.

The digital age has ushered in a new era of communication, one where the boundaries between human and machine are becoming increasingly blurred. Artificial Intelligence (AI) technology, in its relentless evolution, has given rise to remarkable language models that can understand and generate human-like text. "Prompt Engineering for ChatGPT," demystifies the intricacies of this ground breaking technology, offering insights and strategies to harness its capabilities.

This book is ideal for individual investors, financial analysts, portfolio managers, and anyone interested in gaining a deeper understanding of stock market investing. It demystifies the complexities of the stock market, offering insightful strategies and practical advice for investors of all levels. Key topics include laying the groundwork of investing through research, numerous buying strategies, techniques for selling to maximize returns and minimize losses, and using AI integration to master the nuances of risk management. The book covers a wide array of topics to equip you with the knowledge and tools necessary for successful stock investing.

FEATURES:

• Explores the impact of artificial intelligence on stock market investing and how to leverage it for better decision-making
• Covers foundational concepts to advanced topics to provide a thorough understanding of stock market dynamics
• Discusses numerous buying and selling techniques for maximizing returns and minimizing losses