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contents/frameworks/frameworks.html

@@ -1647,7 +1647,7 @@ <h3 data-number="6.8.3" class="anchored" data-anchor-id="library"><span class="h
 <section id="choosing-the-right-framework" class="level2" data-number="6.9">
 <h2 data-number="6.9" class="anchored" data-anchor-id="choosing-the-right-framework"><span class="header-section-number">6.9</span> Choosing the Right Framework</h2>
 <p>Choosing the right machine learning framework for a given application requires carefully evaluating models, hardware, and software considerations. By analyzing these three aspects—models, hardware, and software—ML engineers can select the optimal framework and customize it as needed for efficient and performant on-device ML applications. The goal is to balance model complexity, hardware limitations, and software integration to design a tailored ML pipeline for embedded and edge devices.</p>
-<div id="fig-tf-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-align="center" data-caption="TensorFlow Framework Comparison - General">
+<div id="fig-tf-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-caption="TensorFlow Framework Comparison - General" data-align="center">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image4.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - General" class="figure-img">
@@ -1663,7 +1663,7 @@ <h3 data-number="6.9.1" class="anchored" data-anchor-id="model"><span class="hea
 </section>
 <section id="software" class="level3" data-number="6.9.2">
 <h3 data-number="6.9.2" class="anchored" data-anchor-id="software"><span class="header-section-number">6.9.2</span> Software</h3>
-<div id="fig-tf-sw-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-align="center" data-caption="TensorFlow Framework Comparison - Model">
+<div id="fig-tf-sw-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-caption="TensorFlow Framework Comparison - Model" data-align="center">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-sw-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image5.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - Model" class="figure-img">
@@ -1677,7 +1677,7 @@ <h3 data-number="6.9.2" class="anchored" data-anchor-id="software"><span class="
 </section>
 <section id="hardware" class="level3" data-number="6.9.3">
 <h3 data-number="6.9.3" class="anchored" data-anchor-id="hardware"><span class="header-section-number">6.9.3</span> Hardware</h3>
-<div id="fig-tf-hw-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-align="center" data-caption="TensorFlow Framework Comparison - Hardware">
+<div id="fig-tf-hw-comparison" class="quarto-float quarto-figure quarto-figure-center anchored" data-caption="TensorFlow Framework Comparison - Hardware" data-align="center">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-tf-hw-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image3.png" style="width:100.0%" data-align="center" data-caption="TensorFlow Framework Comparison - Hardware" class="figure-img">
@@ -1723,7 +1723,7 @@ <h2 data-number="6.10" class="anchored" data-anchor-id="future-trends-in-ml-fram
 <section id="decomposition" class="level3" data-number="6.10.1">
 <h3 data-number="6.10.1" class="anchored" data-anchor-id="decomposition"><span class="header-section-number">6.10.1</span> Decomposition</h3>
 <p>Currently, the ML system stack consists of four abstractions as shown in <a href="#fig-mlsys-stack" class="quarto-xref">Figure&nbsp;<span>6.11</span></a>, namely (1) computational graphs, (2) tensor programs, (3) libraries and runtimes, and (4) hardware primitives.</p>
-<div id="fig-mlsys-stack" class="quarto-float quarto-figure quarto-figure-center anchored" data-align="center" data-caption="Four Abstractions in Current ML System Stack">
+<div id="fig-mlsys-stack" class="quarto-float quarto-figure quarto-figure-center anchored" data-caption="Four Abstractions in Current ML System Stack" data-align="center">
 <figure class="quarto-float quarto-float-fig figure">
 <div aria-describedby="fig-mlsys-stack-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <img src="images/png/image8.png" class="img-fluid figure-img" data-align="center" data-caption="Four Abstractions in Current ML System Stack">

contents/hw_acceleration/hw_acceleration.html

@@ -1292,7 +1292,7 @@ <h5 class="anchored" data-anchor-id="power-inefficiency-under-heavy-workloads">P
 </section>
 <section id="comparison" class="level3" data-number="10.3.6">
 <h3 data-number="10.3.6" class="anchored" data-anchor-id="comparison"><span class="header-section-number">10.3.6</span> Comparison</h3>
-<p><a href="#tbl-accelerator-comparison" class="quarto-xref">Table&nbsp;<span>10.2</span></a> Compare the different types of hardware features.</p>
+<p><a href="#tbl-accelerator-comparison" class="quarto-xref">Table&nbsp;<span>10.2</span></a> compares the different types of hardware features.</p>
 <div id="tbl-accelerator-comparison" class="striped hover quarto-float quarto-figure quarto-figure-center anchored">
 <figure class="quarto-float quarto-float-tbl figure">
 <figcaption class="quarto-float-caption-top quarto-float-caption quarto-float-tbl" id="tbl-accelerator-comparison-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">

contents/ops/ops.html

@@ -816,8 +816,7 @@ <h3 data-number="13.2.2" class="anchored" data-anchor-id="mlops"><span class="he
 <li><strong>Optimization:</strong> The complexity of configuring machine learning infrastructure motivated the need for MLOps platforms with optimized, ready-made ML infrastructure.</li>
 </ul>
 <p>While DevOps and MLOps share the common goal of automating and streamlining processes, their focus and challenges differ. DevOps primarily deals with the challenges of software development and IT operations. In contrast, MLOps deals with the additional complexities of managing ML models, such as <a href="https://dvc.org/">data versioning</a>, <a href="https://dvc.org/">model versioning</a>, and <a href="https://www.fiddler.ai/">model monitoring</a>. MLOps also requires stakeholder collaboration, including data scientists, engineers, and IT operations.</p>
-<p>While DevOps and MLOps share similarities in their goals and principles, they differ in their focus and challenges. DevOps focuses on improving the collaboration between development and operations teams and automating software delivery. In contrast, MLOps focuses on streamlining and automating the ML lifecycle and facilitating collaboration between data scientists, data engineers, and IT operations.</p>
-<p><a href="#tbl-mlops" class="quarto-xref">Table&nbsp;<span>13.1</span></a> compares and summarizes them side by side.</p>
+<p>While DevOps and MLOps share similarities in their goals and principles, they differ in their focus and challenges. DevOps focuses on improving the collaboration between development and operations teams and automating software delivery. In contrast, MLOps focuses on streamlining and automating the ML lifecycle and facilitating collaboration between data scientists, data engineers, and IT operations. <a href="#tbl-mlops" class="quarto-xref">Table&nbsp;<span>13.1</span></a> compares and summarizes them side by side.</p>
 <div id="tbl-mlops" class="striped hover quarto-float quarto-figure quarto-figure-center anchored">
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 <figcaption class="quarto-float-caption-top quarto-float-caption quarto-float-tbl" id="tbl-mlops-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">

contents/privacy_security/privacy_security.html

@@ -1087,7 +1087,7 @@ <h2 data-number="14.5" class="anchored" data-anchor-id="security-threats-to-ml-h
 <tr class="header">
 <th style="text-align: left;">Threat Type</th>
 <th style="text-align: left;">Description</th>
-<th style="text-align: left;">Relevance to Embedded ML Hardware Security</th>
+<th style="text-align: left;">Relevance to ML Hardware Security</th>
 </tr>
 </thead>
 <tbody>