mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-06-06 14:04:42 -05:00
c8dc692a09
- Create comprehensive learning timeline page showing 60+ years of ML evolution - Visual progress timeline from Perceptron (1957) to TinyMLPerf (2025) - Module progression map with historical context and achievements - Capability checkpoints tracking system integration - Clean up emoji usage in TOC for professional presentation - Add timeline as first item in Getting Started section - Show students exactly what they'll build at each milestone - Connect each module to real historical breakthroughs - Emphasize progression from foundation to production systems
1041 lines
41 KiB
HTML
1041 lines
41 KiB
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<title>Your TinyTorch Journey: From First Neural Network to Modern AI — TinyTorch</title>
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TinyTorch: Build Your Own ML Framework from First Principles
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
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<li class="toctree-l1 current active"><a class="current reference internal" href="#">Your Learning Journey</a></li>
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<li class="toctree-l1"><a class="reference internal" href="usage-paths/serious-development.html">Serious Development</a></li>
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<li class="toctree-l1"><a class="reference internal" href="usage-paths/classroom-use.html">Classroom Use</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">MLP Era Foundation (1980s)</span></p>
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<li class="toctree-l1"><a class="reference internal" href="chapters/01-setup.html">1. Setup</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapters/02-tensor.html">2. Tensors</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapters/03-activations.html">3. Activations</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapters/04-layers.html">4. Layers</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapters/05-dense.html">5. Dense Networks</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">CNN Revolution (1989-1998)</span></p>
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<li class="toctree-l1"><a class="reference internal" href="chapters/06-spatial.html">7. Spatial Convolutions</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapters/09-autograd.html">9. Autograd</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Universal Intelligence (2017+)</span></p>
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<li class="toctree-l1"><a class="reference internal" href="chapters/16-tinygpt.html">16. TinyGPT</a></li>
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<h1>Your TinyTorch Journey: From First Neural Network to Modern AI</h1>
|
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<!-- Table of contents -->
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<div id="print-main-content">
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<div id="jb-print-toc">
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<ul class="visible nav section-nav flex-column">
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#visual-progress-timeline">Visual Progress Timeline</a><ul class="nav section-nav flex-column">
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-complete-journey-60-years-of-ml-evolution">The Complete Journey: 60+ Years of ML Evolution</a></li>
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</ul>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#module-progression-map">Module Progression Map</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#part-i-neural-network-foundations-modules-1-8">Part I: Neural Network Foundations (Modules 1-8)</a></li>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#part-ii-computer-vision-modules-9-10">Part II: Computer Vision (Modules 9-10)</a></li>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#part-iii-language-models-modules-11-14">Part III: Language Models (Modules 11-14)</a></li>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#part-iv-systems-optimization-modules-15-20">Part IV: Systems Optimization (Modules 15-20)</a></li>
|
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</ul>
|
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</li>
|
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#capability-checkpoints">Capability Checkpoints</a></li>
|
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#historical-achievements-youll-recreate">Historical Achievements You’ll Recreate</a><ul class="nav section-nav flex-column">
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-perceptron">1957: The Perceptron</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-xor-problem">1969: The XOR Problem</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-backpropagation-revolution">1986: The Backpropagation Revolution</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-cnn-breakthrough">2012: The CNN Breakthrough</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-transformer-era">2018: The Transformer Era</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#production-ml-systems">2025: Production ML Systems</a></li>
|
||
</ul>
|
||
</li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#start-your-journey">Start Your Journey</a></li>
|
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</ul>
|
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</nav>
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</div>
|
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</div>
|
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</div>
|
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|
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|
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|
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<div id="searchbox"></div>
|
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<article class="bd-article">
|
||
|
||
<section id="your-tinytorch-journey-from-first-neural-network-to-modern-ai">
|
||
<h1>Your TinyTorch Journey: From First Neural Network to Modern AI<a class="headerlink" href="#your-tinytorch-journey-from-first-neural-network-to-modern-ai" title="Link to this heading">#</a></h1>
|
||
<div class="tip admonition">
|
||
<p class="admonition-title">Your Learning Timeline</p>
|
||
<p>Follow the historical evolution of ML while building every breakthrough yourself. Each milestone represents a real achievement you’ll accomplish with your own code.</p>
|
||
</div>
|
||
<section id="visual-progress-timeline">
|
||
<h2>Visual Progress Timeline<a class="headerlink" href="#visual-progress-timeline" title="Link to this heading">#</a></h2>
|
||
<section id="the-complete-journey-60-years-of-ml-evolution">
|
||
<h3>The Complete Journey: 60+ Years of ML Evolution<a class="headerlink" href="#the-complete-journey-60-years-of-ml-evolution" title="Link to this heading">#</a></h3>
|
||
<div class="highlight-mermaid notranslate"><div class="highlight"><pre><span></span>timeline
|
||
title Your TinyTorch Learning Journey: Building ML History
|
||
|
||
section Foundation Era
|
||
1957 Perceptron : Module 04 Complete
|
||
: Build first trainable neural network
|
||
: Linear separability breakthrough
|
||
|
||
1969 XOR Problem : Module 06 Complete
|
||
: Solve "impossible" problem
|
||
: Discover need for hidden layers
|
||
|
||
section Backpropagation Revolution
|
||
1986 MLP & Backprop : Module 08 Complete
|
||
: Train on real MNIST data
|
||
: 95%+ accuracy achievement
|
||
: Automatic differentiation works!
|
||
|
||
section Modern Vision
|
||
2012 CNN Revolution : Module 10 Complete
|
||
: CIFAR-10 CNNs
|
||
: 75%+ accuracy on real images
|
||
: Spatial feature learning
|
||
|
||
section Language Era
|
||
2018 Transformer/GPT : Module 14 Complete
|
||
: Build TinyGPT
|
||
: Generate coherent text
|
||
: Attention is all you need
|
||
|
||
section Systems Optimization
|
||
2025 TinyMLPerf : Module 20 Complete
|
||
: Compete in optimization
|
||
: Profile and accelerate
|
||
: Production-ready systems
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
</section>
|
||
<section id="module-progression-map">
|
||
<h2>Module Progression Map<a class="headerlink" href="#module-progression-map" title="Link to this heading">#</a></h2>
|
||
<section id="part-i-neural-network-foundations-modules-1-8">
|
||
<h3>Part I: Neural Network Foundations (Modules 1-8)<a class="headerlink" href="#part-i-neural-network-foundations-modules-1-8" title="Link to this heading">#</a></h3>
|
||
<p><strong>Timeline: 1957-1986 | 8 weeks</strong></p>
|
||
<div class="pst-scrollable-table-container"><table class="table">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Week</p></th>
|
||
<th class="head"><p>Module</p></th>
|
||
<th class="head"><p>Historical Context</p></th>
|
||
<th class="head"><p>What You Build</p></th>
|
||
<th class="head"><p>Unlock Achievement</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p>1</p></td>
|
||
<td><p>Setup</p></td>
|
||
<td><p>-</p></td>
|
||
<td><p>Development environment</p></td>
|
||
<td><p>Ready to begin journey</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>2</p></td>
|
||
<td><p>Tensor</p></td>
|
||
<td><p>Mathematical foundations</p></td>
|
||
<td><p>N-dimensional arrays with gradients</p></td>
|
||
<td><p>Core data structure</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>3</p></td>
|
||
<td><p>Activations</p></td>
|
||
<td><p>Neuron modeling</p></td>
|
||
<td><p>ReLU, Sigmoid, Softmax</p></td>
|
||
<td><p>Nonlinearity unlocked</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>4</p></td>
|
||
<td><p>Layers</p></td>
|
||
<td><p><strong>1957: Perceptron Era</strong></p></td>
|
||
<td><p>Linear layers, Module system</p></td>
|
||
<td><p>✨ <strong>Build Perceptron!</strong></p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>5</p></td>
|
||
<td><p>Losses</p></td>
|
||
<td><p>Error measurement</p></td>
|
||
<td><p>MSE, CrossEntropy</p></td>
|
||
<td><p>Can measure learning</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>6</p></td>
|
||
<td><p>Autograd</p></td>
|
||
<td><p><strong>1969: XOR Problem</strong></p></td>
|
||
<td><p>Automatic differentiation</p></td>
|
||
<td><p>✨ <strong>Solve XOR!</strong></p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>7</p></td>
|
||
<td><p>Optimizers</p></td>
|
||
<td><p>Gradient descent</p></td>
|
||
<td><p>SGD, Adam</p></td>
|
||
<td><p>Training acceleration</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>8</p></td>
|
||
<td><p>Training</p></td>
|
||
<td><p><strong>1986: Backprop Revolution</strong></p></td>
|
||
<td><p>Complete training loops</p></td>
|
||
<td><p>✨ <strong>Train MNIST MLP!</strong></p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p><strong>Milestone Unlocked</strong>: After Module 8, you can train real neural networks on actual datasets!</p>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="part-ii-computer-vision-modules-9-10">
|
||
<h3>Part II: Computer Vision (Modules 9-10)<a class="headerlink" href="#part-ii-computer-vision-modules-9-10" title="Link to this heading">#</a></h3>
|
||
<p><strong>Timeline: 2012 CNN Revolution | 2 weeks</strong></p>
|
||
<div class="pst-scrollable-table-container"><table class="table">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Week</p></th>
|
||
<th class="head"><p>Module</p></th>
|
||
<th class="head"><p>Historical Context</p></th>
|
||
<th class="head"><p>What You Build</p></th>
|
||
<th class="head"><p>Unlock Achievement</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p>9</p></td>
|
||
<td><p>Spatial</p></td>
|
||
<td><p>Convolution breakthrough</p></td>
|
||
<td><p>Conv2d, MaxPool2d</p></td>
|
||
<td><p>Spatial intelligence</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>10</p></td>
|
||
<td><p>DataLoader</p></td>
|
||
<td><p><strong>2012: AlexNet moment</strong></p></td>
|
||
<td><p>Efficient data pipelines</p></td>
|
||
<td><p>✨ <strong>75%+ CIFAR-10!</strong></p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p><strong>Milestone Unlocked</strong>: Modern computer vision with CNNs on real images!</p>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="part-iii-language-models-modules-11-14">
|
||
<h3>Part III: Language Models (Modules 11-14)<a class="headerlink" href="#part-iii-language-models-modules-11-14" title="Link to this heading">#</a></h3>
|
||
<p><strong>Timeline: 2017-2018 Transformer Era | 4 weeks</strong></p>
|
||
<div class="pst-scrollable-table-container"><table class="table">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Week</p></th>
|
||
<th class="head"><p>Module</p></th>
|
||
<th class="head"><p>Historical Context</p></th>
|
||
<th class="head"><p>What You Build</p></th>
|
||
<th class="head"><p>Unlock Achievement</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p>11</p></td>
|
||
<td><p>Tokenization</p></td>
|
||
<td><p>Text processing</p></td>
|
||
<td><p>Vocabulary building</p></td>
|
||
<td><p>Text to numbers</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>12</p></td>
|
||
<td><p>Embeddings</p></td>
|
||
<td><p>Word representations</p></td>
|
||
<td><p>Token & positional encoding</p></td>
|
||
<td><p>Semantic space</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>13</p></td>
|
||
<td><p>Attention</p></td>
|
||
<td><p>Attention mechanism</p></td>
|
||
<td><p>Multi-head attention</p></td>
|
||
<td><p>Sequence understanding</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>14</p></td>
|
||
<td><p>Transformers</p></td>
|
||
<td><p><strong>2018: GPT Era</strong></p></td>
|
||
<td><p>Complete transformer blocks</p></td>
|
||
<td><p>✨ <strong>TinyGPT works!</strong></p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p><strong>Milestone Unlocked</strong>: Generate text with transformers you built from scratch!</p>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="part-iv-systems-optimization-modules-15-20">
|
||
<h3>Part IV: Systems Optimization (Modules 15-20)<a class="headerlink" href="#part-iv-systems-optimization-modules-15-20" title="Link to this heading">#</a></h3>
|
||
<p><strong>Timeline: Modern ML Engineering | 6 weeks</strong></p>
|
||
<div class="pst-scrollable-table-container"><table class="table">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Week</p></th>
|
||
<th class="head"><p>Module</p></th>
|
||
<th class="head"><p>Historical Context</p></th>
|
||
<th class="head"><p>What You Build</p></th>
|
||
<th class="head"><p>Unlock Achievement</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p>15</p></td>
|
||
<td><p>Profiling</p></td>
|
||
<td><p>Performance analysis</p></td>
|
||
<td><p>Memory & compute profiling</p></td>
|
||
<td><p>Find bottlenecks</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>16</p></td>
|
||
<td><p>Acceleration</p></td>
|
||
<td><p>Hardware optimization</p></td>
|
||
<td><p>Vectorization, caching</p></td>
|
||
<td><p>10x speedups</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>17</p></td>
|
||
<td><p>Quantization</p></td>
|
||
<td><p>Model compression</p></td>
|
||
<td><p>INT8 inference</p></td>
|
||
<td><p>4x memory reduction</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>18</p></td>
|
||
<td><p>Compression</p></td>
|
||
<td><p>Pruning & distillation</p></td>
|
||
<td><p>Sparse models</p></td>
|
||
<td><p>90% size reduction</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>19</p></td>
|
||
<td><p>Caching</p></td>
|
||
<td><p>Memory optimization</p></td>
|
||
<td><p>KV-cache for generation</p></td>
|
||
<td><p>Faster inference</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>20</p></td>
|
||
<td><p>Benchmarking</p></td>
|
||
<td><p><strong>2025: TinyMLPerf</strong></p></td>
|
||
<td><p>Competition framework</p></td>
|
||
<td><p>✨ <strong>Complete Framework!</strong></p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p><strong>Final Achievement</strong>: Production-ready ML systems engineer!</p>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="capability-checkpoints">
|
||
<h2>Capability Checkpoints<a class="headerlink" href="#capability-checkpoints" title="Link to this heading">#</a></h2>
|
||
<p>Track your progress through 16 capability milestones:</p>
|
||
<div class="note admonition">
|
||
<p class="admonition-title">Your Capability Progress</p>
|
||
<p>Each checkpoint represents a fundamental ML systems capability you’ve mastered.</p>
|
||
</div>
|
||
<div class="pst-scrollable-table-container"><table class="table">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Checkpoint</p></th>
|
||
<th class="head"><p>Capability Question</p></th>
|
||
<th class="head"><p>Modules Required</p></th>
|
||
<th class="head"><p>Status</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p>00</p></td>
|
||
<td><p>Can I set up my environment?</p></td>
|
||
<td><p>01</p></td>
|
||
<td><p>⬜ Setup</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>01</p></td>
|
||
<td><p>Can I manipulate tensors?</p></td>
|
||
<td><p>02</p></td>
|
||
<td><p>⬜ Foundation</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>02</p></td>
|
||
<td><p>Can I add nonlinearity?</p></td>
|
||
<td><p>03</p></td>
|
||
<td><p>⬜ Intelligence</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>03</p></td>
|
||
<td><p>Can I build network layers?</p></td>
|
||
<td><p>04</p></td>
|
||
<td><p>⬜ Components</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>04</p></td>
|
||
<td><p>Can I measure loss?</p></td>
|
||
<td><p>05</p></td>
|
||
<td><p>⬜ Networks</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>05</p></td>
|
||
<td><p>Can I compute gradients?</p></td>
|
||
<td><p>06</p></td>
|
||
<td><p>⬜ Learning</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>06</p></td>
|
||
<td><p>Can I optimize parameters?</p></td>
|
||
<td><p>07</p></td>
|
||
<td><p>⬜ Optimization</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>07</p></td>
|
||
<td><p>Can I train models?</p></td>
|
||
<td><p>08</p></td>
|
||
<td><p>⬜ Training</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>08</p></td>
|
||
<td><p>Can I process images?</p></td>
|
||
<td><p>09</p></td>
|
||
<td><p>⬜ Vision</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>09</p></td>
|
||
<td><p>Can I load data efficiently?</p></td>
|
||
<td><p>10</p></td>
|
||
<td><p>⬜ Data</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>10</p></td>
|
||
<td><p>Can I process text?</p></td>
|
||
<td><p>11</p></td>
|
||
<td><p>⬜ Language</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>11</p></td>
|
||
<td><p>Can I create embeddings?</p></td>
|
||
<td><p>12</p></td>
|
||
<td><p>⬜ Representation</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>12</p></td>
|
||
<td><p>Can I implement attention?</p></td>
|
||
<td><p>13</p></td>
|
||
<td><p>⬜ Attention</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>13</p></td>
|
||
<td><p>Can I build transformers?</p></td>
|
||
<td><p>14</p></td>
|
||
<td><p>⬜ Architecture</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>14</p></td>
|
||
<td><p>Can I profile performance?</p></td>
|
||
<td><p>15-19</p></td>
|
||
<td><p>⬜ Systems</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>15</p></td>
|
||
<td><p>Can I optimize and compete?</p></td>
|
||
<td><p>20</p></td>
|
||
<td><p>⬜ Mastery</p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p>Use <code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">checkpoint</span> <span class="pre">status</span></code> to see your real-time progress!</p>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="historical-achievements-youll-recreate">
|
||
<h2>Historical Achievements You’ll Recreate<a class="headerlink" href="#historical-achievements-youll-recreate" title="Link to this heading">#</a></h2>
|
||
<section id="the-perceptron">
|
||
<h3>1957: The Perceptron<a class="headerlink" href="#the-perceptron" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: Build the first trainable neural network</p>
|
||
<ul class="simple">
|
||
<li><p>Frank Rosenblatt’s revolutionary machine</p></li>
|
||
<li><p>Proves machines can learn from examples</p></li>
|
||
<li><p>Foundation for all modern AI</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="the-xor-problem">
|
||
<h3>1969: The XOR Problem<a class="headerlink" href="#the-xor-problem" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: Solve the “impossible” problem</p>
|
||
<ul class="simple">
|
||
<li><p>Minsky & Papert’s challenge that stopped AI research</p></li>
|
||
<li><p>Demonstrates need for hidden layers</p></li>
|
||
<li><p>Your solution proves multi-layer networks work</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="the-backpropagation-revolution">
|
||
<h3>1986: The Backpropagation Revolution<a class="headerlink" href="#the-backpropagation-revolution" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: Train on real handwritten digits</p>
|
||
<ul class="simple">
|
||
<li><p>Rumelhart, Hinton & Williams unlock deep learning</p></li>
|
||
<li><p>95%+ accuracy on MNIST</p></li>
|
||
<li><p>Automatic differentiation changes everything</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="the-cnn-breakthrough">
|
||
<h3>2012: The CNN Breakthrough<a class="headerlink" href="#the-cnn-breakthrough" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: 75%+ accuracy on CIFAR-10</p>
|
||
<ul class="simple">
|
||
<li><p>AlexNet moment for computer vision</p></li>
|
||
<li><p>Spatial features dominate vision tasks</p></li>
|
||
<li><p>Your CNN matches modern baselines</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="the-transformer-era">
|
||
<h3>2018: The Transformer Era<a class="headerlink" href="#the-transformer-era" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: Generate text with TinyGPT</p>
|
||
<ul class="simple">
|
||
<li><p>Attention mechanisms revolutionize NLP</p></li>
|
||
<li><p>Universal architecture for all modalities</p></li>
|
||
<li><p>Your implementation generates coherent text</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="production-ml-systems">
|
||
<h3>2025: Production ML Systems<a class="headerlink" href="#production-ml-systems" title="Link to this heading">#</a></h3>
|
||
<p><strong>Your Achievement</strong>: Complete optimization pipeline</p>
|
||
<ul class="simple">
|
||
<li><p>Profile, optimize, and deploy</p></li>
|
||
<li><p>TinyMLPerf competition framework</p></li>
|
||
<li><p>You’re now an ML systems engineer</p></li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="start-your-journey">
|
||
<h2>Start Your Journey<a class="headerlink" href="#start-your-journey" title="Link to this heading">#</a></h2>
|
||
<p>Ready to begin? Start with <a class="reference internal" href="chapters/01-setup.html"><span class="std std-doc">Module 01: Setup</span></a> and begin building your own ML framework from scratch!</p>
|
||
<div class="tip admonition">
|
||
<p class="admonition-title">Track Your Progress</p>
|
||
<p>Use the TinyTorch CLI to track your journey:</p>
|
||
<ul class="simple">
|
||
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">checkpoint</span> <span class="pre">status</span></code> - See your capability progress</p></li>
|
||
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">checkpoint</span> <span class="pre">timeline</span></code> - Visualize your learning path</p></li>
|
||
<li><p><code class="docutils literal notranslate"><span class="pre">tito</span> <span class="pre">module</span> <span class="pre">complete</span> <span class="pre">XX</span></code> - Complete modules and unlock achievements</p></li>
|
||
</ul>
|
||
</div>
|
||
<p><strong>Remember</strong>: You’re not just learning ML - you’re recreating 60+ years of breakthroughs with your own hands. Each line of code you write is building toward complete ML systems mastery.</p>
|
||
</section>
|
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</section>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-complete-journey-60-years-of-ml-evolution">The Complete Journey: 60+ Years of ML Evolution</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#part-i-neural-network-foundations-modules-1-8">Part I: Neural Network Foundations (Modules 1-8)</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#capability-checkpoints">Capability Checkpoints</a></li>
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|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-perceptron">1957: The Perceptron</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-xor-problem">1969: The XOR Problem</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-backpropagation-revolution">1986: The Backpropagation Revolution</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-cnn-breakthrough">2012: The CNN Breakthrough</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-transformer-era">2018: The Transformer Era</a></li>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#production-ml-systems">2025: Production ML Systems</a></li>
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|
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#start-your-journey">Start Your Journey</a></li>
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