From dc9f38b5936ae286b81dff232358a34ed344d7a9 Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Fri, 18 Jul 2025 10:38:45 -0400 Subject: [PATCH] =?UTF-8?q?=F0=9F=93=9A=20Improve=20resources=20page=20org?= =?UTF-8?q?anization=20and=20add=20tinyML=20course?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 🎓 Course Additions: - Added CS 249r: Tiny Machine Learning (Harvard) to course list - Covers TinyML systems, edge AI, and resource-constrained machine learning - Complements existing MIT TinyML course with Harvard perspective 📖 Section Naming Fix: - Changed 'Essential Books' → 'Recommended Books' - Avoids prescriptive language and duplication issues - More inclusive and less hierarchical phrasing 🔄 Organization Benefits: - Eliminates potential confusion with ML Systems book already in courses - Creates clearer separation between course materials and supplementary books - Better reflects that these are helpful additions, not requirements Result: More thoughtful resource organization with key Harvard tinyML course addition and improved section naming. --- book/resources.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/book/resources.md b/book/resources.md index f9ade480..09ce99a8 100644 --- a/book/resources.md +++ b/book/resources.md @@ -15,9 +15,12 @@ While TinyTorch teaches you to build ML systems from scratch, these resources pr - **[Machine Learning Systems](https://mlsysbook.ai)** by Prof. Vijay Janapa Reddi (Harvard) *Comprehensive systems perspective on ML engineering and optimization* -- **[CS 6.S965: TinyML and Efficient Deep Learning](https://hanlab.mit.edu/courses/2023-fall-65.2420/)** (MIT) +- **[CS 6.S965: TinyML and Efficient Deep Learning](https://hanlab.mit.edu/courses/2024-fall-65940)** (MIT) *Edge computing, model compression, and efficient ML algorithms* +- **[CS 249r: Tiny Machine Learning](https://sites.google.com/g.harvard.edu/tinyml/home)** (Harvard) + *TinyML systems, edge AI, and resource-constrained machine learning* + ### **Deep Learning Foundations** - **[CS 231n: Convolutional Neural Networks](http://cs231n.stanford.edu/)** (Stanford) *Computer vision and CNN architectures - complements TinyTorch spatial modules* @@ -27,7 +30,7 @@ While TinyTorch teaches you to build ML systems from scratch, these resources pr --- -## 📖 **Essential Books** +## 📖 **Recommended Books** ### **Systems & Engineering** - **"Designing Machine Learning Systems"** by Chip Huyen