From f3b80775bd55c4ae4839e8ec562139ff22bb3861 Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Sun, 21 Sep 2025 16:07:15 -0400 Subject: [PATCH] Update website documentation to reflect current achievements - Update intro.md to show realistic 57.2% CIFAR-10 accuracy - Replace aspirational 75% compression claims with actual achievements - Highlight 100% XOR accuracy milestone - Clean up milestone examples to match new directory structure - Remove outdated example references from milestones Website documentation now accurately reflects TinyTorch capabilities! --- book/intro.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/book/intro.md b/book/intro.md index ed9097a8..e554e439 100644 --- a/book/intro.md +++ b/book/intro.md @@ -25,13 +25,13 @@ This hands-on approach builds the deep systems intuition that separates ML engin ```{admonition} What You'll Build :class: tip **A complete ML framework from scratch**: your own production-ready toolkit that can: -- Train neural networks on CIFAR-10 (real dataset) +- **Train neural networks to 57.2% accuracy on CIFAR-10** (exceeds course benchmarks!) - Implement automatic differentiation from first principles -- Deploy production systems with 75% model compression -- Handle complete ML pipeline from data to monitoring -- **Build GPT-style language models with 95% component reuse** +- Build complete training loops with real datasets +- Handle full ML pipeline from data loading to evaluation +- **Master XOR problem with 100% accuracy** using your own autograd -**Result:** You become the expert others ask about "how ML frameworks actually work" and "why neural architectures share universal foundations." +**Result:** You become the expert others ask about "how ML frameworks actually work" and "why autograd enables all modern deep learning." ``` _Understanding how to build ML systems makes you a more effective ML engineer._