Design Patterns in Machine Learning
Unlock the power of AI and machine learning with a guide that bridges theory and practice. Design Patterns in Machine Learning is more than just another machine learning textbook-it's a roadmap for building scalable, reliable, and ethical systems.Through proven machine learning design patterns, practical machine learning questions, and hands-on strategies, this book equips you to navigate real-world challenges such as data drift, reproducibility, and model deployment at scale. Whether you're exploring machine learning with Python, diving deep into machine learning and AI, or advancing into the frontiers of machine learning deep learning, you'll find the tools you need to succeed.Each chapter distills complex concepts into actionable insights: from embedding layers and hyperparameter tuning to reproducible workflows and fairness frameworks. With step-by-step explanations, coding examples in machine learning Python, and real-world use cases, you'll accelerate your career while mastering the craft of modern AI.Perfect for data scientists, developers, and innovators, this book gives you the design patterns to transform ideas into resilient solutions-and keep you at the forefront of AI machine learning.
Data Governance with Unity Catalog on Databricks
Organizations collecting and using personal data must now heed a growing body of regulations, and the penalties for noncompliance are stiff. The ubiquity of the cloud and the advent of generative AI have only made it more crucial to govern data appropriately. Thousands of companies have turned to Databricks Unity Catalog to simplify data governance and manage their data and AI assets more effectively. This practical guide helps you do the same. Databricks data specialists Kiran Sreekumar and Karthik Subbarao dive deep into Unity Catalog and share the best practices that enable data practitioners to build and serve their data and AI assets at scale. Data product owners, data engineers, AI/ML engineers, and data executives will examine various facets of data governance--including data sharing, auditing, access controls, and automation--as they discover how to establish a robust data governance framework that complies with regulations. Explore data governance fundamentals and understand how they relate to Unity Catalog Utilize Unity Catalog to unify data and AI governance Access data efficiently for analytics Implement different data protection mechanisms Securely share data and AI assets internally and externally with Delta Sharing Disclaimer: This book is not written by or on behalf of Databricks, and the views/opinions expressed in the book do not necessarily represent the views/opinions of Databricks.
Providing Integrity, Awareness, and Consciousness in Distributed Dynamic Systems
AI for Beginners
Master AI fundamentals faster than you ever thought possible, even if you are new to tech!Are you eager to unlock the potential of AI but overwhelmed by the sheer volume of information out there? Do you want to harness AI to boost your career, but feel daunted by technical jargon?AI for Beginners is the key to demystifying AI and unlocking your potential to use AI wisely and resourcefully.Here's a glimpse of what you'll find inside: The essentials to kick-start your AI journey without an advanced tech background.Discover AI tools that are suited for beginners and why they work.A guide blending theory and practice for a balanced understanding.How AI can transform everyday challenges into solutions with practical implementations.An exploration of how AI is transforming sectors from healthcare to education.How to stay updated on the latest AI trends with minimal time investment.Discover how artificial intelligence could shape industries, societies, and the global economy in the years to come.With this book, you won't just learn AI; you'll understand how to apply it in real-world contexts and make it a powerful element of your personal and professional development.
ChatGPT for Beginners Made Easy
Unlock Your Potential with ChatGPT - No Tech Expertise Required!Whether you're brand new to ChatGPT or already experimenting with AI and ready to level up, ChatGPT for Beginners Made Easy gives you the tools, prompts, and workflows to turn curiosity into confidence-and turn AI into a powerful asset in your daily life.This practical, beginner-friendly guide is designed for real-world results: save time, get more done, and build a skill you can actually monetize.What You'll Learn: Get started fast: Learn to use ChatGPT in under 30 minutesWrite better prompts: Craft powerful, reusable prompts that work across AI platformsPlan goals, projects, and your day: Build personal productivity workflows with ChatGPTLearn and solve problems: Research, study, and work through real-world challengesWrite with AI: Plan, draft, and revise content more efficientlyAutomate your workflows: Build your own custom GPTs for recurring tasksBoost productivity: Save time on everything from email to brainstormingMake money with AI: Explore over 10 beginner-friendly monetization strategiesStart strong: Includes 200+ free prompts to get you going immediatelyThis book strips away the complexity and shows you how to actually use AI-clearly, quickly, and with confidence.By the end, you'll have: A streamlined system to get more done in less timeA practical skill set you can monetize in multiple waysThe ability to adapt to future AI tools with easeReady to simplify AI and unlock what it can do for you?
Reversible Computation
This book constitutes the refereed proceedings of the 17th International Conference on Reversible Computation, RC 2025, held in Odense, Denmark, during July 3-4, 2025. The 7 full papers and 5 short papers included in this book were carefully reviewed and selected from 22 submissions.The conference brought together researchers from computer science, mathematics, engineering, and physics to discuss new developments and directions for future research in the area of Reversible Computation.
Edge Intelligence in Cyber-Physical Systems
Edge Intelligence in Cyber-Physical Systems: Foundations and Applications provides a comprehensive overview of best practices for building edge intelligence into cyber-physical systems. This book covers the foundations and applications of synergizing machine learning at the edge of CPS, leveraging an edge computing infrastructure. Divided into four parts, the first section of the book reviews the foundations, principles, and representative application domains of CPS. The second part covers machine learning, edge computing, and their needs in CPS, defining edge intelligence and its principles, challenges, and research directions. The third part presents tutorials and foundational research works on realizing edge intelligence in representative CPS. The fourth part explores the problem space of threats and countermeasures in building edge intelligence into CPS. Researchers, graduate students and professionals in computer science, data science, and electrical engineering will find this to be a valuable resource on the principles and applications of edge intelligence in cyber-physical systems as well as the development of interdisciplinary techniques to advance the field.
AI Hacking and Exploitation
Uncover the intricate world of AI Hacking and Exploitation!This is an essential guide for understanding vulnerabilities in AI systems.Delve into direct overwrite injection, instructional prefixing, and recursive self-injection.Explore techniques like subtextual injection, role reassignment, and evasive low-level methods.Master the art of detecting and mitigating refusal behaviors, memory vulnerabilities, and jailbreak methodologies.Enhance your knowledge on model mimicry, output manipulation, temporal exploits, and morePerfect for AI researchers and developers, this comprehensive taxonomy offers strategies, case studies, and solutions to safeguard AI systems against potential threats.
Artificial Intelligence All-In-One for Dummies
A comprehensive roadmap to using AI in your career and in your life Artificial intelligence is everywhere. Major software organizations like Microsoft, Google, and Apple have built AI directly into products and invited the world to become part of the AI revolution. And it's impossible to use these tools to their fullest potential without understanding the basics of what AI is and what it can do. Artificial Intelligence All-in-One For Dummies compiles insight from the expert authors of AI books in the For Dummies series to provide an easy-to-follow walkthrough for anyone interested in learning how to use AI. You'll learn how to put artificial intelligence to work for you and your company in a wide variety of situations, from creating office assistants to managing projects and marketing your products. Inside the book: How to prompt AI platforms like ChatGPT and Copilot while avoiding "hallucinations" and other bugs Strategies for adding artificial intelligence tools to your company's existing workflows to improve efficiency and generate new opportunities Techniques to improve your programming capabilities with AI or create new AI-powered tools Perfect for professionals curious about the potential and pitfalls associated with generative artificial intelligence, Artificial Intelligence All-in-One For Dummies shows you exactly how AI works and how you can apply it in your own professional and personal life.
Dataproc Cookbook
Want to build big data solutions in Google Cloud? Dataproc Cookbook is your hands-on guide to mastering Dataproc and the essential GCP fundamentals--like networking, security, monitoring, and cost optimization--that apply across Google Cloud services. Learn practical skills that not only fast-track your Dataproc expertise, but also help you succeed with a wide range of GCP technologies. Written by data experts Narasimha Sadineni and Anu Venkataraman, this cookbook tackles real-world use cases like serverless Spark jobs, Kubernetes-native deployments, and cost-optimized data lake workflows. You'll learn how to create ephemeral and persistent Dataproc clusters, run secure data science workloads, implement monitoring solutions, and plan effective migration and optimization strategies. Create Dataproc clusters on Compute Engine and Kubernetes Engine Run data science workloads on Dataproc Execute Spark jobs on Dataproc Serverless Optimize Dataproc clusters to be cost effective and performant Monitor Spark jobs in various ways Orchestrate various workloads and activities Use different methods for migrating data and workloads from existing Hadoop clusters to Dataproc
Ultimate Beginner’s Guide to AI
Future-proof your career with AI-no tech skills required.Feeling overwhelmed by the complexity of artificial intelligence? Worried about how it might impact your job?Afraid you're already falling behind the competition? This practical, empowering guide is designed for professionals like you: ambitious, curious, and eager to stay ahead, even if you're not a "tech person." In Ultimate Beginner's Guide to AI, you'll find a clear, jargon-free path to understanding and applying artificial intelligence in your career and daily life. Whether you're in marketing, healthcare, education, business, or any other field, this book will show you how to confidently embrace the tools and ideas shaping tomorrow.Inside, you'll discover: The essential building blocks of AI, machine learning, and natural language processing.More than 200 sample prompts to explore the range and power of AI.Practical exercises that let you apply AI knowledge immediately, enhancing your learning experience.How to integrate AI into your workflow for increased productivity without needing a tech background.The best AI tools you can start using today to improve both personal and professional efficiency.Strategies for leveraging AI to drive career growth and secure your future in a tech-driven world.How to start learning AI with no technical background and still achieve success.The ethical considerations of AI and how they impact both the workplace and society at large.Time-efficient learning modules designed for busy adults, so you can learn at your own pace.Exclusive downloadable resources that provide additional support and deepen your understanding.How to connect with a community of AI learners, creating a supportive network around your new skills. ...and much more!You don't need to be a data scientist or software engineer. You just need a willingness to learn-and a few minutes a day. Whether you want to boost your productivity, explore new career paths, or simply understand the tech shaping your future, this guide is your practical starting point.
Cutting-Edge Artificial Intelligence Advances and Implications in Real-World Applications
Artificial Intelligence (AI) is impacting industries worldwide by introducing new methods and altering traditional practices. This book examines AI's diverse effects, providing insights into its applications, challenges, and future prospects across education, healthcare, finance, and more.The chapters explore how AI technologies, such as large language models, enhance feedback in higher education and influence legal studies while upholding academic integrity. A review of key technical approaches--knowledge-based systems, machine learning, and intelligent optimization--lays the groundwork for understanding AI's potential. Real-world examples illustrate AI's role in medical imaging, presenting new diagnostic methods and the use of language models for image interpretation. The book also discusses financial applications, including techniques for credit card fraud detection and forecasting natural gas prices using innovative models. Additionally, it covers personalized federated learning models, highlighting the importance of data privacy and security in AI's evolution.This comprehensive guide is valuable for educators, researchers, practitioners, and students interested in AI's current and future developments. By combining theory with practical examples, the book offers readers a clear understanding of how AI affects various sectors, enabling them to engage effectively with this rapidly evolving field.
Cutting-Edge Artificial Intelligence Advances and Implications in Real-World Applications
Artificial Intelligence (AI) is impacting industries worldwide by introducing new methods and altering traditional practices. This book examines AI's diverse effects, providing insights into its applications, challenges, and future prospects across education, healthcare, finance, and more.The chapters explore how AI technologies, such as large language models, enhance feedback in higher education and influence legal studies while upholding academic integrity. A review of key technical approaches--knowledge-based systems, machine learning, and intelligent optimization--lays the groundwork for understanding AI's potential. Real-world examples illustrate AI's role in medical imaging, presenting new diagnostic methods and the use of language models for image interpretation. The book also discusses financial applications, including techniques for credit card fraud detection and forecasting natural gas prices using innovative models. Additionally, it covers personalized federated learning models, highlighting the importance of data privacy and security in AI's evolution.This comprehensive guide is valuable for educators, researchers, practitioners, and students interested in AI's current and future developments. By combining theory with practical examples, the book offers readers a clear understanding of how AI affects various sectors, enabling them to engage effectively with this rapidly evolving field.
Time Molecules
Time is not just a measure-it's the key to unlocking the hidden patterns that drive every system, from business intelligence to AI-powered decision-making.In Time Molecules, Eugene Asahara introduces a business intelligence-inspired extension to process mining and systems thinking, blending Markov models, event logs, and AI-driven analytics to further enhance the cooperation of our human intelligence with enterprise intelligence. This book challenges traditional BI methods by shifting the focus from static snapshots of data to the fluid, interconnected nature of processes, empowering decision-makers to anticipate change, optimize workflows, and drive efficiency at scale.Built on decades of experience in OLAP cubes, dimensional modeling, and data-driven strategy, Time Molecules provides BI professionals, data engineers, and executives with the tools to model and analyze event-driven processes using a scalable, probabilistic framework. By treating time as the central dimension and events as molecular building blocks, Asahara demonstrates how Markov models can be applied at scale, offering a powerful method to transform raw data into actionable business intelligence.Readers will explore how businesses, like living organisms, thrive through interconnected systems of processes, evolving dynamically in response to market forces, competition, and operational inefficiencies. Through process mining, digital twins, and AI-powered insights, Time Molecules reveals how organizations can uncover inefficiencies, optimize decision-making, and build resilience in an ever-changing world.The book covers a wide range of topics essential for modern data professionals, including the integration of Markov models with traditional BI, leveraging the astonishing versatility of AI and large language models (LLMs), and applying systems thinking to complex business operations. From case studies in logistics, sales, and customer behavior to real-world implementations using SQL-based TimeSolution architecture, Time Molecules bridges theory and practice in an accessible and insightful manner.With an emphasis on real-time analytics and predictive modeling, this book highlights how businesses can move beyond simple metrics like sums and counts to more sophisticated probabilistic forecasting. It explores how slicing and dicing event sequences across multiple dimensions provides a deeper understanding of customer journeys, operational bottlenecks, and hidden correlations in large-scale data environments.Time Molecules also delves into the impact of AI on business intelligence, illustrating how machine learning models can enhance process mining and decision automation. It discusses the limitations of large language models (LLMs) in business operations and presents Markov models as a transparent and efficient alternative for time-based data analysis.Designed for data professionals seeking to elevate their BI capabilities, this book serves as both a practical guide and a conceptual roadmap for mastering the art of process-driven intelligence. Whether you are a BI engineer, a CDO, or an executive navigating digital transformation, Time Molecules offers a structured approach to understanding the complexities of modern business processes.With AI and automation redefining industries at an astounding and accelerating rate, Time Molecules is a must-read for anyone looking to future-proof their business intelligence strategy.
Introduction to Database Systems Modeling and Administration
Master the art of Data Modeling and SQL Administration with this comprehensive guide!In today's data-driven world, the ability to design and manage efficient database systems is essential for IT professionals. Introduction to Database Systems Modeling and Administration offers a structured approach to understanding database fundamentals, SQL programming, and data modeling best practices. This book bridges the gap between theory and practical application by covering fundamental topics such as data modeling, normalization, and entity-relationship diagrams, all while introducing real-world database management principles. It includes step-by-step instructions on how to use MySQL, MariaDB, SQLite, and Microsoft SQL Server, making it an invaluable resource for working with different database platforms.Designed to align with the Ohio Department of Education's Transfer Acceptance Guide (TAG) for database management courses, this book ensures that readers develop industry-standard competencies. By following DAMA-DMBOK(R) guidelines, it presents modeling techniques that enhance clarity and efficiency when structuring databases for enterprise applications.Through hands-on exercises and case studies, readers will learn how to design relational databases, optimize queries, and implement best practices in database security and administration. From conceptual and logical modeling to advanced SQL queries and stored procedures, every topic is explained with clear examples and practical scenarios.You'll master the key principles of data integrity, indexing strategies, and database transactions, ensuring you can create robust and scalable systems. With detailed explanations of data structures, attributes, and relationships, you'll gain the skills needed to translate business requirements into well-structured databases. This knowledge is essential for anyone working with enterprise data, business intelligence, or software development.By the end of this book, you will be equipped with the knowledge and confidence to model, design, and administer databases effectively, ensuring you can optimize performance, maintain data consistency, and support business operations with well-structured database solutions.If you're ready to take your database skills to the next level and gain a deep understanding of relational data modeling and SQL, Introduction to Database Systems Modeling and Administration is the guide you need to unlock your full potential!
Start a Business with AI & Using AI to Make Money
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Data Analysis with Llms
Speed up common data science tasks with AI assistants like ChatGPT and Large Language Models (LLMs) from Anthropic, Cohere, Open AI, Google, Hugging Face, and more! Data Analysis with LLMs teaches you to use the new generation of AI assistants and Large Language Models (LLMs) to aid and accelerate common data science tasks. Learn how to use LLMs to: - Analyze text, tables, images, and audio files - Extract information from multi-modal data lakes - Classify, cluster, transform, and query multimodal data - Build natural language query interfaces over structured data sources - Use LangChain to build complex data analysis pipelines - Prompt engineering and model configuration All practical, Data Analysis with LLMs takes you from your first prompts through advanced techniques like creating LLM-based agents for data analysis and fine-tuning existing models. You'll learn how to extract data, build natural language query interfaces, and much more. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Large Language Models (LLMs) can streamline and accelerate almost any data science task. Master the techniques in this book, and you'll be able to analyze large amounts of text, tabular and graph data, images, videos, and more with clear natural language prompts and a few lines of Python code. About the book Data Analysis with LLMs shows you exactly how to integrate generative AI into your day-to-day work as a data scientist. In it, Cornell professor Immanuel Trummer guides you through a series of engaging projects that introduce OpenAI's Python library, tools like LangChain and LlamaIndex, and LLMs from Anthropic, Cohere, and Hugging Face. As you go, you'll use AI to query structured and unstructured data, analyze sound and images, and optimize the cost and quality of your data analysis process. What's inside - Classify, cluster, transform, and query multimodal data - Build natural language query interfaces over structured data sources - Create LLM-based agents for autonomous data analysis - Prompt engineering and model configuration About the reader For data scientists and data analysts who know the basics of Python. About the author Immanuel Trummer is an associate professor of computer science at Cornell University and a member of the Cornell Database Group. Table of Contents Part 1 1 Analyzing data with large language models 2 Chatting with ChatGPT Part 2 3 The OpenAI Python library 4 Analyzing text data 5 Analyzing structured data 6 Analyzing images and videos 7 Analyzing audio data Part 3 8 GPT alternatives 9 Optimizing cost and quality 10 Software frameworks
Ultimate Apache Superset for Data Visualization and Analytics
Apache Superset to Master Data Visualization and Build High-Impact BI Solutions Book DescriptionApache Superset is a powerful open-source data visualization and business intelligence platform that enables professionals to create interactive dashboards effortlessly. With its user-friendly interface and broad compatibility with various data sources, Superset helps users uncover insights and make informed, data-driven decisions in real time. Ultimate Apache Superset for Data Visualization and Analytics offers a structured, hands-on approach to mastering Apache Superset. It begins with installation and configuration, guiding you through building your first visualization and dashboard. As you progress, you'll explore advanced features such as SQL Lab, custom visualizations, and security management. The book also covers optimizing dashboards, integrating Superset with data pipelines, and deploying it in production environments. Each chapter includes practical examples, best practices, and real-world use cases to reinforce learning. By the end, you'll have the expertise to build high-impact, interactive dashboards and confidently deploy Apache Superset in production. Whether you're a data analyst, engineer, or business professional, this book equips you with the skills to scale and customize Superset for your organization's needs. Don't get left behind-unlock the full potential of Apache Superset and take your data visualization to the next level! Table of Contents1. Introduction to Apache Superset2. Installing and Configuring Apache Superset3. Getting Started with Data Visualization4. Data Exploration and SQL Lab5. Custom Visualizations and Plugins6. Security and Access Control7. Building and Optimizing Dashboards8. Integrating Superset into Data Pipelines9. Exploratory Data Analysis and Hypothesis Testing10. Scaling and Deploying Superset in Production11. Superset for Business Reporting12. Self-Service BI with Superset13. Emerging Trends and Innovations in Data Visualization Index
Mathematical Entity Linking Methods and Applications
This research book explores the adaptation of traditional Entity Linking techniques to Mathematical Entity Linking (MathEL) for STEM disciplines, addressing the limitations of current Information Retrieval methods in handling mathematical expressions. By developing and evaluating novel MathEL approaches using AI, Machine Learning, and the Wikidata Knowledge Graph, significant progress is achieved in areas such as Formula Concept recognition, semantic formula search, mathematical question answering, physics exam question generation, and STEM document classification. The study also introduces a suite of open-source Wikimedia MathEL tools, including AnnoMathTeX, MathQA, and PhysWikiQuiz, designed to advance Mathematical Information Retrieval and support innovative applications in academic and educational contexts.
Artificial Intelligence for Business
Understand and harness the power of artificial intelligence to drive growth and innovation with this comprehensive guide. As AI continues to evolve, it is increasingly important for businesses to make informed decisions about how to use AI to drive success and growth. This book aims to provide a comprehensive understanding of AI and its applications in business, making it the ideal resource for business managers and leaders looking to stay ahead of the curve. With a focus on practical applications and real-world examples, it helps readers understand what AI is, how it is transforming business, how it can be used to drive growth and innovation and how to navigate the realities of implementation. This book looks at the combination of AI with other emerging technologies such as blockchain, internet of things and virtual and augmented reality, showing how these can work together to create new business opportunities and solve complex business problems. It provides guidance on the importance of designing AI applications that are human-centred, including inclusive design and empathy in AI. It features contributions and insights from leading experts and a wealth of real-world examples profiling AI adoption and innovation.
Artificial Intelligence for Business
Understand and harness the power of artificial intelligence to drive growth and innovation with this comprehensive guide. As AI continues to evolve, it is increasingly important for businesses to make informed decisions about how to use AI to drive success and growth. This book aims to provide a comprehensive understanding of AI and its applications in business, making it the ideal resource for business managers and leaders looking to stay ahead of the curve. With a focus on practical applications and real-world examples, it helps readers understand what AI is, how it is transforming business, how it can be used to drive growth and innovation and how to navigate the realities of implementation. This book looks at the combination of AI with other emerging technologies such as blockchain, internet of things and virtual and augmented reality, showing how these can work together to create new business opportunities and solve complex business problems. It provides guidance on the importance of designing AI applications that are human-centred, including inclusive design and empathy in AI. It features contributions and insights from leading experts and a wealth of real-world examples profiling AI adoption and innovation.
Artificial Intelligence and Its Applications
This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence and its Applications, ICAIA 2023, held in Pune, India, during December 18-19, 2023. The 37 full papers and 3 short papers presented in these two volumes were carefully reviewed and selected from 217 submissions. The conference focused on three primary domains: Use of AI in Health Care; Machine Vision and Image Processing; Automated and Digital Manufacturing Systems.
AWS Certified Data Engineer Associate Study Guide
There's no better time to become a data engineer. And acing the AWS Certified Data Engineer Associate (DEA-C01) exam will help you tackle the demands of modern data engineering and secure your place in the technology-driven future. Authors Sakti Mishra, Dylan Qu, and Anusha Challa equip you with the knowledge and sought-after skills necessary to effectively manage data and excel in your career. Whether you're a data engineer, data analyst, or machine learning engineer, you'll discover in-depth guidance, practical exercises, sample questions, and expert advice needed to leverage AWS services effectively and achieve certification. Ingest, transform, and orchestrate data pipelines effectively Select the ideal data store, design efficient data models, and manage data lifecycles Analyze data rigorously and maintain high data quality standards Implement robust authentication, authorization, and data governance protocols Prepare thoroughly for the DEA-C01 exam with targeted strategies and practices
Implementing Analytics Solutions Using Microsoft Fabric-DP-600 Exam Study Guide
