From b68c3a454136e85f21cadb06b0001ac61bf10b95 Mon Sep 17 00:00:00 2001 From: Josefine Hansson <66409231+jhansson-ard@users.noreply.github.com> Date: Tue, 25 Oct 2022 08:17:34 +0200 Subject: [PATCH] Updated link [MKC-745] --- .../get-started-with-machine-learning.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/hardware/03.nano/boards/nano-33-ble-sense/tutorials/get-started-with-machine-learning/get-started-with-machine-learning.md b/content/hardware/03.nano/boards/nano-33-ble-sense/tutorials/get-started-with-machine-learning/get-started-with-machine-learning.md index 8da96a621e..d65c714bf7 100644 --- a/content/hardware/03.nano/boards/nano-33-ble-sense/tutorials/get-started-with-machine-learning/get-started-with-machine-learning.md +++ b/content/hardware/03.nano/boards/nano-33-ble-sense/tutorials/get-started-with-machine-learning/get-started-with-machine-learning.md @@ -483,4 +483,4 @@ For added fun the [Emoji_Button.ino](https://github.com/arduino/ArduinoTensorFlo ## Conclusion It’s an exciting time with a lot to learn and explore in TinyML. We hope this blog has given you some idea of the potential and a starting point to start applying it in your own projects. Be sure to let us know what you build and [share it](https://create.arduino.cc/projecthub) with the Arduino community. -For a comprehensive background on TinyML and the example applications in this article, we recommend Pete Warden and Daniel Situnayake’s new O’Reilly book “[TinyML: Machine Learning with TensorFlow on Arduino and Ultra-Low Power Microcontrollers](https://books.google.com/books/about/TinyML.html?id=sB3mxQEACAAJ&source=kp_book_description).” \ No newline at end of file +For a comprehensive background on TinyML and the example applications in this article, we recommend Pete Warden and Daniel Situnayake’s new O’Reilly book “[TinyML: Machine Learning with TensorFlow on Arduino and Ultra-Low Power Microcontrollers](https://www.oreilly.com/library/view/tinyml/9781492052036/).”