diff --git a/docs/contents/conventions.qmd b/docs/contents/conventions.qmd deleted file mode 100644 index 109fc7e5..00000000 --- a/docs/contents/conventions.qmd +++ /dev/null @@ -1,68 +0,0 @@ -# Conventions Used in this Book - -Please follow these conventions as you contribute to this online book: - -1. **Clear Structure and Organization:** - - - **Chapter Outlines:** Begin each chapter with an outline that provides an - overview of the topics covered. - - **Sequential Numbering:** Utilize sequential numbering for chapters, - sections, and subsections to facilitate easy reference. - -2. **Accessible Language:** - - - **Glossary:** Include a glossary that defines technical terms and jargon. - - **Consistent Terminology:** Maintain consistent use of terminology - throughout the book to avoid confusion. - -3. **Learning Aids:** - - - **Diagrams and Figures:** Employ diagrams, figures, and tables to visually - convey complex concepts. - - **Sidebars:** Use sidebars for additional information, anecdotes, or to - provide real-world context to the theoretical content. - -4. **Interactive Elements:** - - - **Colabs and Projects:** Integrate exercises and projects at the end of - each chapter to encourage active learning and practical application of - concepts. - - **Case Studies:** Incorporate case studies to provide a deeper - understanding of how principles are applied in real-world situations. - -5. **References and Further Reading:** - - - **Bibliography:** Include a bibliography at the end of each chapter for - readers who wish to dive deeper into specific topics. - - **Citations:** Maintain a consistent style for citations, adhering to - recognized academic standards like APA, MLA, or Chicago. - -6. **Supporting Materials:** - - - **Supplementary Online Resources:** Provide links to supplementary online - resources, such as video lectures, webinars, or interactive modules. - - **Datasets and Code Repositories:** Share datasets and code repositories - for hands-on practice, particularly for sections dealing with algorithms - and applications. - -7. **Feedback and Community Engagement:** - - - **Forums and Discussion Groups:** Establish forums or discussion groups - where readers can interact, ask questions, and share knowledge. - - **Open Review Process:** Implement an open review process, inviting - feedback from the community to continuously improve the content. - -8. **Inclusivity and Accessibility:** - - - **Inclusive Language:** Utilize inclusive language that respects diversity - and promotes equality. - - **Accessible Formats:** Ensure the textbook is available in accessible - formats, including audio and Braille, to cater to readers with - disabilities. - -9. **Index:** - - **Comprehensive Index:** Include a comprehensive index at the end of the - book to help readers quickly locate specific information. - -Implementing these conventions can contribute to creating a textbook that is -comprehensive, accessible, and conducive to effective learning. diff --git a/docs/index.html b/docs/index.html index 50375485..57da3105 100644 --- a/docs/index.html +++ b/docs/index.html @@ -595,7 +595,6 @@

Table of contents

  • Preface
  • Why We Wrote This Book
  • What You’ll Need to Know
  • -
  • Book Conventions
  • Content Transparency Statement
  • Want to Help Out?
  • Get in Touch
  • @@ -671,10 +670,6 @@

    Why We Wrote This Book

    What You’ll Need to Know

    To dive into this book, you don’t need to be an AI expert. All you need is a basic understanding of computer science concepts and a curiosity to explore how AI systems work. This is where innovation happens, and a basic grasp of programming and data structures will be your compass.

    -
    -

    Book Conventions

    -

    For details on the conventions used in this book, check out the Conventions section.

    -

    Content Transparency Statement

    This book is a community-driven project, with content generated collaboratively by numerous contributors over time. The content creation process may have involved various editing tools, including generative AI technology. As the main author, editor, and curator, Prof. Vijay Janapa Reddi maintains human oversight and editorial oversight to make sure the content is accurate and relevant. However, no one is perfect, so inaccuracies may still exist. We highly value your feedback and encourage you to provide corrections or suggestions. This collaborative approach is crucial for enhancing and maintaining the quality of the content contained within and making high-quality information globally accessible.

    diff --git a/docs/search.json b/docs/search.json index 5dbd4e50..bad8b626 100644 --- a/docs/search.json +++ b/docs/search.json @@ -4,7 +4,7 @@ "href": "index.html", "title": "Machine Learning Systems", "section": "", - "text": "Preface\nWelcome to Machine Learning Systems. This book is your gateway to the fast-paced world of AI systems. It is an extension of the course CS249r at Harvard University.\n\nWe have created this open-source book as a collaborative effort to bring together insights from students, professionals, and the broader community of AI practitioners. Our goal is to develop a comprehensive guide that explores the intricacies of AI systems and their numerous applications.\n\n“If you want to go fast, go alone. If you want to go far, go together.” – African Proverb\n\nThis isn’t a static textbook; it’s a living, breathing document. We’re making it open-source and continuously updated to meet the ever-changing needs of this dynamic field. Expect a rich blend of expert knowledge that guides you through the complex interplay between cutting-edge algorithms and the foundational principles that make them work. We’re setting the stage for the next big leap in AI innovation.\n\n\nWhy We Wrote This Book\nWe’re in an age where technology is always evolving. Open collaboration and sharing knowledge are the building blocks of true innovation. That’s the spirit behind this effort. We go beyond the traditional textbook model to create a living knowledge hub, so that we can all share and learn from one another.\nThe book focuses on AI systems’ principles and case studies, aiming to give you a deep understanding that will help you navigate the ever-changing landscape of AI systems. By keeping it open, we’re not just making learning accessible but inviting new ideas and ongoing improvements. In short, we’re building a community where knowledge is free to grow and light the way forward in global AI technology.\n\n\nWhat You’ll Need to Know\nTo dive into this book, you don’t need to be an AI expert. All you need is a basic understanding of computer science concepts and a curiosity to explore how AI systems work. This is where innovation happens, and a basic grasp of programming and data structures will be your compass.\n\n\nBook Conventions\nFor details on the conventions used in this book, check out the Conventions section.\n\n\nContent Transparency Statement\nThis book is a community-driven project, with content generated collaboratively by numerous contributors over time. The content creation process may have involved various editing tools, including generative AI technology. As the main author, editor, and curator, Prof. Vijay Janapa Reddi maintains human oversight and editorial oversight to make sure the content is accurate and relevant. However, no one is perfect, so inaccuracies may still exist. We highly value your feedback and encourage you to provide corrections or suggestions. This collaborative approach is crucial for enhancing and maintaining the quality of the content contained within and making high-quality information globally accessible.\n\n\nWant to Help Out?\nIf you’re interested in contributing, you can find the guidelines here.\n\n\nGet in Touch\nDo you have questions or feedback? Feel free to e-mail Prof. Vijay Janapa Reddi directly, or you are welcome to start a discussion thread on GitHub.\n\n\nContributors\nA big thanks to everyone who’s helped make this book what it is! You can see the full list of individual contributors here and additional GitHub style details here. Join us as a contributor!", + "text": "Preface\nWelcome to Machine Learning Systems. This book is your gateway to the fast-paced world of AI systems. It is an extension of the course CS249r at Harvard University.\n\nWe have created this open-source book as a collaborative effort to bring together insights from students, professionals, and the broader community of AI practitioners. Our goal is to develop a comprehensive guide that explores the intricacies of AI systems and their numerous applications.\n\n“If you want to go fast, go alone. If you want to go far, go together.” – African Proverb\n\nThis isn’t a static textbook; it’s a living, breathing document. We’re making it open-source and continuously updated to meet the ever-changing needs of this dynamic field. Expect a rich blend of expert knowledge that guides you through the complex interplay between cutting-edge algorithms and the foundational principles that make them work. We’re setting the stage for the next big leap in AI innovation.\n\n\nWhy We Wrote This Book\nWe’re in an age where technology is always evolving. Open collaboration and sharing knowledge are the building blocks of true innovation. That’s the spirit behind this effort. We go beyond the traditional textbook model to create a living knowledge hub, so that we can all share and learn from one another.\nThe book focuses on AI systems’ principles and case studies, aiming to give you a deep understanding that will help you navigate the ever-changing landscape of AI systems. By keeping it open, we’re not just making learning accessible but inviting new ideas and ongoing improvements. In short, we’re building a community where knowledge is free to grow and light the way forward in global AI technology.\n\n\nWhat You’ll Need to Know\nTo dive into this book, you don’t need to be an AI expert. All you need is a basic understanding of computer science concepts and a curiosity to explore how AI systems work. This is where innovation happens, and a basic grasp of programming and data structures will be your compass.\n\n\nContent Transparency Statement\nThis book is a community-driven project, with content generated collaboratively by numerous contributors over time. The content creation process may have involved various editing tools, including generative AI technology. As the main author, editor, and curator, Prof. Vijay Janapa Reddi maintains human oversight and editorial oversight to make sure the content is accurate and relevant. However, no one is perfect, so inaccuracies may still exist. We highly value your feedback and encourage you to provide corrections or suggestions. This collaborative approach is crucial for enhancing and maintaining the quality of the content contained within and making high-quality information globally accessible.\n\n\nWant to Help Out?\nIf you’re interested in contributing, you can find the guidelines here.\n\n\nGet in Touch\nDo you have questions or feedback? Feel free to e-mail Prof. Vijay Janapa Reddi directly, or you are welcome to start a discussion thread on GitHub.\n\n\nContributors\nA big thanks to everyone who’s helped make this book what it is! You can see the full list of individual contributors here and additional GitHub style details here. Join us as a contributor!", "crumbs": [ "FRONT MATTER", "Preface"