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How to get started with TensorFlow Lite for Microcontrollers e1682739928777

How to get started with TensorFlow Lite for Microcontrollers

Want to build your own TinyML application? This is a detailed approach to getting started with TensorFlow Lite for Microcontrollers! Story Introduction In the summer of 2022 I was selected to participate in the Google Summer of Code (GSoC) under TensorFlow. While trying to build my firstΒ project,Β I quickly realized that there weren’t many good beginner

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Metal Detecting with PIC18 Q71 Microcontroller e1681189004799

Metal Detecting with PIC18-Q71 Microcontroller

Distinguish between metal and non-metallic objects using Core Independent Peripherals (CIPs) with the Metal Detecting with PIC18-Q71 Microcontroller. Story about Metal Detecting with PIC18-Q71 This application creates a simpleΒ proximityΒ metal detector with the Core Independent Peripherals (CIPs) in theΒ PIC18-Q71 family of microcontrollers (MCUs)Β to differentiate between metallic and non-metallic objects placed near the detector coil. The CIPs

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TensorFlow Lite for Microcontrollers Part 2 e1681182224432

In-depth: TensorFlow Lite for Microcontrollers – Part 2

This blog details the inner workings of TensorFlow Lite for Microcontrollers and the role of Flatbuffers in them. Story of TensorFlow Lite for Microcontrollers Part 2/2:Β This blog extends myΒ TensorFlow Lite for Microcontrollers tutorial.Β I was selected in Google Summer of Code, under TensorFlow, to work on building demos for TinyML and when I read through the

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Pinguino Project A PIC Microcontroller Based Arduino e1681100158848

Pinguino Project: A PIC Microcontroller Based Arduino

This is a complete tutorial to make a PIC Microcontroller based Arduino. This is a complete tutorial to make PIC microcontroller basedΒ Arduino, which can run Arduino programs onΒ PIC18F4550Β orΒ PIC18F2550Β microcontroller, one advantage on this microcontroller is that it doesn’t require any external programmers, since it has inbuilt USB support. So guys, let’s get started! Step 1: Things

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