Re organizing

harvard-edge · Jun 18, 2024 · 109c2e4 · 109c2e4
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diff --git a/contents/labs/labs.qmd b/contents/labs/labs.qmd
@@ -1,6 +1,6 @@
 # Overview {.unnumbered}
 
-Welcome to the hands-on labs section where you'll explore deploying machine learning models onto real embedded devices, offering a practical introduction to ML systems. Unlike traditional approaches with large-scale models, these labs focus on interacting directly with both hardware and software. They help us show case various sensor modalities across different application use cases. This approach provides valuable insights into the challenges and opportunities of deploying AI on real physical systems.
+Welcome to the hands-on labs section where you'll explore deploying ML models onto real embedded devices, which will offer a practical introduction to ML systems. Unlike traditional approaches with large-scale models, these labs focus on interacting directly with both hardware and software. They help us show case various sensor modalities across different application use cases. This approach provides valuable insights into the challenges and opportunities of deploying AI on real physical systems.
 
 ## Learning Objectives
 
@@ -32,6 +32,16 @@ These labs are designed for:
 
 * **Enthusiasts and researchers** who want to gain practical experience in deploying AI on edge devices and understand the unique challenges involved.
 
+## Supported Devices
+
+| Exercise                          | [Nicla Vision](https://store.arduino.cc/products/nicla-vision)                    | [XIAO ESP32S3](https://www.google.com/search?q=XIAO+ESP32S3)                    |
+| --------------------------------- | ------------------------------- | ------------------------------- |
+| Installation & Setup              | ✅                              | ✅                              |
+| Keyword Spotting (KWS)            | ✅                              | ✅                              |
+| Image Classification              | ✅                              | ✅                              |
+| Object Detection                  | ✅                              | ✅                              |
+| Motion Detection                  | ✅                              | ✅                              |
+
 ## Lab Structure
 
 Each lab follows a structured approach:
@@ -45,17 +55,7 @@ Each lab follows a structured approach:
 4. **Exercises**: Hands-on tasks to modify and experiment with model parameters.
 
 5. **Discussion**: Analysis of results, potential improvements, and practical insights.
-
-## Supported Devices
-
-| Exercise                          | [Nicla Vision](https://store.arduino.cc/products/nicla-vision)                    | [XIAO ESP32S3](https://www.google.com/search?q=XIAO+ESP32S3)                    |
-| --------------------------------- | ------------------------------- | ------------------------------- |
-| Installation & Setup              | ✅                              | ✅                              |
-| Keyword Spotting (KWS)            | ✅                              | ✅                              |
-| Image Classification              | ✅                              | ✅                              |
-| Object Detection                  | ✅                              | ✅                              |
-| Motion Detection                  | ✅                              | ✅                              |
-
+
 ## Troubleshooting and Support
 
 If you encounter any issues during the labs, consult the troubleshooting comments or check the FAQs within each lab. For further assistance, feel free to reach out to our support team or engage with the community forums.