Merge pull request #1 from harvard-edge/topic/setup

Topic/setup

_quarto.yml

@@ -3,43 +3,75 @@ project:
   output-dir: _book
 
 book:
+  page-navigation: true
   title: "Embedded AI: Principles, Algorithms, and Applications"
+  search: true
+  repo-url: https://github.com/harvard-edge/cs249r_book.git
+  repo-actions: [edit, issue, source]
+  downloads: [pdf, epub]
+  sharing: [twitter, facebook]
   reader-mode: true
   cover-image: cover.png
   favicon: cover.png
   page-footer:
     left: |
-      Embedded AI written and edited by Vijay Janapa Reddi and Song Han.
+      Embedded AI edited by Prof. Vijay Janapa Reddi (Harvard University) and Prof. Song Han (MIT).
     right: |
       This book was built with <a href="https://quarto.org/">Quarto</a>.
-  author: "Vijay Janapa Reddi (Harvard University) and Song Han (MIT)"
-  date: "9/5/2023"
+
   chapters:
     - index.qmd
+    - credits.qmd
     - about.qmd
+    - dedication.qmd
     - introduction.qmd
-    - tinyml.qmd
-    - primer.qmd
+    - dl_primer.qmd
+    - embedded_sys.qmd
+    - embedded_ml.qmd
     - mlworkflow.qmd
-    - datacollection.qmd
+    - data_engineering.qmd
     - preprocessing.qmd
-    - feature_engineering.qmd
+    - frameworks.qmd
     - training.qmd
+    - efficient_ai.qmd
     - optimizations.qmd
     - deployment.qmd
+    - ondevice_learning.qmd
+    - hw_acceleration.qmd
     - mlops.qmd
+    - sustainable_ai.qmd
+    - responsible_ai.qmd
+    - generative_ai.qmd
     - references.qmd
+    - acknowledgements.qmd
 appendices:
+    - case_studies.qmd
     - tools.qmd
     - resources.qmd
 
 bibliography: references.bib
 
+keywords:
+  - open-source
+  - embedded systems
+  - machine learning
+  - tinyML
+license: CC-BY-NC
+
+crossref:
+  appendix-title: "App."
+  appendix-delim: ":"
+
+
 format:
   html:
     theme: zephyr
   pdf:
     documentclass: scrreprt
-
-
-
+    include-in-header: 
+      text: |
+        \usepackage{makeidx}
+        \makeindex
+    include-after-body: 
+      text: |
+        \printindex

acknowledgements.qmd

@@ -0,0 +1,3 @@
+# Acknowledgements {.unnumbered}
+
+coming soon.

case_studies.qmd

@@ -0,0 +1,3 @@
+# Case Studies
+
+coming soon.

conventions.md

@@ -0,0 +1,40 @@
+# 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**:
+   - **Exercises 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 delve 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.

credits.qmd

@@ -0,0 +1,3 @@
+# Credits {.unnumbered}
+
+coming soon.

data_engineering.qmd

@@ -1,4 +1,4 @@
-# Data Collection
+# Data Engineering
 
 ## Data Sources
 

dl_primer.qmd

@@ -1,4 +1,4 @@
-# Deep Learning Primer
+# Deep Learning
 
 ## What are Neural Networks
 

efficient_ai.qmd

@@ -0,0 +1,3 @@
+# Efficient AI
+
+coming soon.

embedded_sys.qmd

@@ -0,0 +1,7 @@
+# Embedded Systems
+
+## Sensors
+
+## Power
+
+coming soon.

feature_engineering.qmd

@@ -1,3 +0,0 @@
-# Feature Engineering
-
-coming soon.

frameworks.qmd

@@ -0,0 +1,3 @@
+# ML Frameworks
+
+coming soon.

generative_ai.qmd

@@ -0,0 +1,3 @@
+# Generative AI
+
+coming soon.

hw_acceleration.qmd

@@ -0,0 +1,3 @@
+# Hardware Acceleration
+
+coming soon.

index.qmd

@@ -1,15 +1,33 @@
 # Preface {.unnumbered}
 
-This is a Quarto book.
+In "Embedded AI: Principles, Algorithms, and Applications", we will embark on a critical exploration of the rapidly evolving field of artificial intelligence in the context of embedded systems, originally nurtured from the foundational course, tinyML from CS249r. 
 
-To learn more about Quarto books visit <https://quarto.org/docs/books>.
+The goal of this book is to bring about a collaborative endeavor with insights and contributions from students, practitioners and the wider community, blossoming into a comprehensive guide that delves into the principles governing embedded AI and its myriad applications. 
+
+As a living document, this open-source textbook aims to bridge gaps and foster innovation by being globally accessible and continually updated, addressing the pressing need for a centralized resource in this dynamic field. With a rich tapestry of knowledge woven from various expert perspectives, readers can anticipate a guided journey that unveils the intricate dance between cutting-edge algorithms and the principles that ground them, paving the way for the next wave of technological transformation.
 
 # The Philosophy Behind the Book
 
+We live in a world where technology perpetually reshapes itself, fostering an ecosystem of open collaboration and knowledge sharing stands as the cornerstone of innovation. This philosophy fuels the creation of "Embedded AI: Principles, Algorithms, and Applications." This is a venture that transcends conventional textbook paradigms to foster a living repository of knowledge. Anchoring its content on principles, algorithms, and applications, the book aims to cultivate a deep-rooted understanding that empowers individuals to navigate the fluid landscape of embedded AI with agility and foresight. By embracing an open approach, we not only democratize learning but also pave avenues for fresh perspectives and iterative enhancements, thus fostering a community where knowledge is not confined but is nurtured to grow, adapt, and illuminate the path of progress in embedded AI technologies globally.
+
 # Prerequisites
 
+Venturing into "Embedded AI: Principles, Algorithms, and Applications" does not mandate you to be a maestro in machine learning from the outset. At its core, this resource seeks to nurture learners who bear a fundamental understanding of systems and harbor a curiosity to explore the confluence of disparate, yet interconnected domains: embedded hardware, artificial intelligence, and software. This confluence forms a vibrant nexus where innovations and new knowledge streams emerge, making a basic grounding in system operations a pivotal tool in navigating this dynamic space.
+
+Moreover, the goal of this book is to delve into the synergies created at the intersection of these fields, fostering a learning environment where the boundaries of traditional disciplines blur to give way to a holistic, integrative approach to modern technological innovations. Your interest in unraveling embedded AI technologies and low-level software mechanics would be guiding you through a rich learning experience. 
+
 # Conventions Used in This Book
 
+Please follow the conventions listed in [Conventions](./conventions.md)
+
 # How to Contact Us
 
+Please contact _vj@eecs.harvard.edu_
+
+# How to Contribute
+
+Please see instructions at [here](https://github.com/harvard-edge/cs249r_book).
+
 # Contributors
+
+Please see [Credits](./credits.md).

mlworkflow.qmd

@@ -1,4 +1,4 @@
-# Machine Learning Workflow
+# ML Workflow
 
 ## Data Collection
 

ondevice_learning.qmd

@@ -0,0 +1,7 @@
+# On-Device Learning
+
+## Federated Learning
+
+## On-Device Training
+
+coming soon.

privacy_security.qmd

@@ -0,0 +1,3 @@
+# Privacy and Security
+
+coming soon.

responsible_ai.qmd

@@ -0,0 +1,3 @@
+# Responsible AI
+
+coming soon.

sustainable_ai.qmd

@@ -0,0 +1,3 @@
+# AI Sustainability
+
+coming soon.

tools.qmd

@@ -1,2 +1,2 @@
-# Tools
+# Tools {.appendix}